Patent Publication Number: US-9839403-B2

Title: Medical imaging apparatus and method for processing medical image

Description:
RELATED APPLICATION(S) 
     This application claims the benefit of Korean Patent Application No. 10-2014-0169972, filed on Dec. 1, 2014, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein in its entirety by reference. 
     BACKGROUND 
     Present disclosure relates to a medical imaging apparatus and a method of processing a medical image, and more particularly, to a medical imaging apparatus and a method of processing a medical image to alleviate image deterioration. 
     A medical imaging apparatus is used to acquire an image of an internal structure of an object. The medical imaging apparatus, which is a non-invasive test apparatus, provides a user with medical information by imaging and processing structural details, internal tissues, or a fluid flow in a human body. A user, such as a medical doctor, may check and diagnose the health and disease state of a patient based on medical images from a medical imaging apparatus. 
     A typical medical imaging apparatus may be an X-ray apparatus or a computed tomography (CT) apparatus. An X-ray apparatus is a medical apparatus used to acquire an image of an internal structure of a human body by transmitting an X-ray through the human body. Compared to other medical apparatuses such as a magnetic resonance imaging (MRI) apparatus or a CT apparatus, the X-ray apparatus has merit in that a medical image of an object may be acquired within a short time. Accordingly, the X-ray apparatus has been widely used for normal imaging of chest, abdomen, skeleton, sinus, neck soft tissue, and breasts as well as other body parts. 
     A CT apparatus, which may provide a sectional image of an object, may provide images of internal organs such as kidney or lung, without overlapping them with other organs. 
     Both the X-ray apparatus and the CT apparatus acquire a medical image by transmitting an X-ray through an object. However, it is known that exposure to high doses of X-ray can damage body parts. Accordingly, a medical imaging apparatus and a method of processing a medical image whereby a high quality medical image may be acquired by exposing the object to a reduced amount of X-rays are needed. 
     SUMMARY 
     One or more exemplary embodiments include a medical imaging apparatus and a method of processing a medical image, which may improve quality of a medical image 
     Additional aspects will be set forth in part in the description which follows and, in part, will be apparent from the description, or may be learned by practice of the presented exemplary embodiments. 
     According to one or more exemplary embodiments, a medical imaging apparatus includes a data acquirer configured to acquire measured data acquired by detecting X-ray transmitted by an X-ray source to an object, and an image processor configured to acquire an initial image based on the measured data, estimate a region of interest (ROI)-outside measured data and an ROI-inside measured data based on the measured data and the initial image, and acquire a reconstructed image based on the ROI-inside measured data. 
     The image processor may be further configured to estimate a difference between data acquired by re-projecting an inside of an ROI in the initial image and the measured data as the ROI-outside measured data, and acquire an ROI-outside image based on the ROI-outside measured data and estimate a difference between data acquired by re-projecting the ROI-outside image and the measured data as the ROI-inside measured data. 
     The image processor may be further configured to acquire an ROI-inside image based on the ROI-inside measured data, determine whether to update the ROI-outside measured data and the ROI-inside measured data, and when it is determined to update the ROI-outside measured data and the ROI-inside measured data, the image processor updates the ROI-outside measured data based on the ROI-inside image, the ROI-inside measured data based on the updated ROI-outside measured data, and the ROI-inside image based on the updated ROI-inside measured data. 
     The image processor may be further configured to iteratively perform an update operation including updating the ROI-outside measured data, updating the ROI-inside measured data, and updating the ROI-inside image until it is determined to stop updating the ROI-outside measured data and the ROI-inside measured data, and acquire the reconstructed image based on a finally updated ROI-inside image, where the finally updated ROI-inside image is the ROI-inside image updated just prior to being determined to stop updating the ROI-outside measured data and the ROI-inside measured data. 
     The image processor may be configured to stop the update operation when a difference between the ROI-inside measured data and data acquired by re-projecting the ROI-inside image acquired based on the ROI-inside measured data is less than a threshold value. 
     The image processor may be configured to stop the update operation after repeating the update operation a predetermined number of times. 
     The medical imaging apparatus may further include an input unit configured to receive an input for determining the predetermined number of times for repeating the update operation. 
     The medical imaging apparatus may further include an output unit configured to output at least one of the ROI-inside image and the updated ROI-inside image, and an input unit configured to receive an input as to whether the output ROI-inside image is approved, wherein when the input received through the input unit indicates that the output ROI-inside image is approved, the image processor stops the update operation. 
     The medical imaging apparatus may further include an input unit configured to receive a parameter related to estimation or updating the ROI-outside measured data. 
     The image processor may be further configured to acquire the ROI-outside image based on the ROI-outside measured data by an iterative reconstruction technique and acquire the ROI-inside image based on the ROI-inside measured data by the iterative reconstruction technique. 
     The image processor may be further configured to acquire the initial image based on the measured data by using at least one of an analytical reconstruction technique and an iterative reconstruction technique. 
     The image processor may be further configured to acquire the initial image by removing an outside of the ROI from an image reconstructed based on the measured data. 
     The image processor may be further configured to estimate a difference between data acquired by re-projecting an outside of an ROI in the initial image and the measured data as initial ROI-inside measured data, acquire an initial ROI-inside image based on the initial ROI-inside measured data and estimate a difference between data acquired by re-projecting the ROI-inside image and the measured data as the ROI-outside measured data, and acquire an ROI-outside image based on the ROI-outside measured data and estimate a difference between data acquired by re-projecting the ROI-outside image and the measured data as the ROI-inside measured data. 
     The image processor is configured to acquire an ROI-inside image based on the ROI-inside measured data, determine whether to update the ROI-outside measured data and the ROI-inside measured data, and when it is determined to update the ROI-outside measured data and the ROI-inside measured data, the image processor updates the ROI-outside measured data based on the ROI-inside image, the ROI-inside measured data based on the updated ROI-outside measured data, the ROI-inside image based on the updated ROI-inside measured data. 
     The image processor may be further configured to iteratively perform an update operation including updating the ROI-outside measured data, updating the ROI-inside measured data, and updating the ROI-inside image until it is determined to stop updating the ROI-outside measured data and the ROI-inside measured data, and acquire the reconstructed image based on the finally updated ROI-inside image, wherein the finally updated ROI-inside image is the ROI-inside image updated just prior to being determined to stop updating the ROI-outside measured data and the ROI-inside measured data. 
     The measured data may be at least one of truncated data and data acquired at a low radiation dose of the X-ray transmitted by the X-ray source, wherein the low radiation dose is less than a reference value. 
     The medical imaging apparatus may further include a detector configured to rotate with the X-ray source and detect the X-ray. 
     The medical imaging apparatus may further include a C-arm having one end connected to the X-ray source and another end connected to the detector. 
     The medical imaging apparatus may further include a gantry including the X-ray source and the detector. 
     The data acquirer may include a communication unit configured to receive the measured data from a medical apparatus including the X-ray source. 
     According to one or more exemplary embodiments, a method of operating a medical image apparatus includes acquiring measured data acquired by detecting X-ray transmitted by an X-ray source to an object, acquiring an initial image based on the measured data, estimating a region of interest (ROI)-outside measured data and an ROI-inside measured data based on the measured data and the initial image, and acquiring a reconstructed image based on the ROI-inside measured data. 
     The estimating of the ROI-outside measured data and ROI-inside measured data may include estimating a difference between data acquired by re-projecting an inside of an ROI in the initial image and the measured data as the ROI-outside measured data, and acquiring an ROI-outside image based on the ROI-outside measured data and estimating a difference between data acquired by re-projecting the ROI-outside image and the measured data as the ROI-inside measured data. 
     The method may further include acquiring an ROI-inside image based on the ROI-inside measured data, determining whether to update the ROI-outside measured data and the ROI-inside measured data, and when it is determined to update the ROI-outside measured data and the ROI-inside measured data, updating the ROI-outside measured data based on the ROI-inside image, updating the ROI-inside measured data based on the updated ROI-outside measured data, and updating the ROI-inside image based on the updated ROI-inside measured data. 
     An update operation including updating the ROI-outside measured data, updating the ROI-inside measured data, and updating the ROI-inside image until it is determined to stop updating the ROI-outside measured data and the ROI-inside measured data, and acquire the reconstructed image based on a finally updated ROI-inside image, wherein the finally updated ROI-inside image is the ROI-inside image updated just prior to being determined to stop updating the ROI-outside measured data and the ROI-inside measured data. 
     The update operation may be stopped when a difference between the ROI-inside measured data and data acquired by re-projecting the ROI-inside image acquired based on the ROI-inside measured data is less than a threshold value. 
     The update operation may be stopped after the update operation is repeated a predetermined number of times. 
     The method may further include receiving, from a user, an input about information for determining the predetermined number of times for repeating the update operation. 
     The method may further include outputting the ROI-inside image or the updated ROI-inside image, and receiving an input as to whether the output ROI-inside image is approved, wherein upon receiving the input indicating that the output ROI-inside image is approved, the image processor stops the update operation. 
     The method may further include receiving a parameter related to estimation or updating the ROI-outside measured data. 
     The ROI-outside image may be acquired based on the ROI-outside measured data by an iterative reconstruction technique, and the ROI-inside image may be acquired based on the ROI-inside measured data by the iterative reconstruction technique. 
     The initial image may be acquired based on the measured data by an analytical reconstruction technique or an iterative reconstruction technique. 
     The initial image may be acquired by removing an outside of a ROI from an image reconstructed based on the measured data. 
     The alternately estimating of the ROI-outside measured data and ROI-inside measured data may include estimating a difference between data acquired by re-projecting an outside of ROI in the initial image and the measured data as initial ROI-inside measured data, acquiring an initial ROI-inside image based on the initial ROI-inside measured data and estimating a difference between data acquired by re-projecting the ROI-inside image and the measured data as the ROI-outside measured data, and acquiring an ROI-outside image based on the ROI-outside measured data and estimating a difference between data acquired by re-projecting the ROI-outside image and the measured data as the ROI-inside measured data. 
     The measured data may be at least one of truncated data and data acquired at a low radiation dose of the X-ray transmitted by the X-ray source, wherein the low radiation dose is less than a reference value. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       These and/or other aspects will become apparent and more readily appreciated from the following description of the exemplary embodiments, taken in conjunction with the accompanying drawings in which: 
         FIG. 1  illustrates an X-ray apparatus according to an exemplary embodiment; 
         FIG. 2  illustrates a structure of the X-ray apparatus of  FIG. 1 ; 
         FIG. 3  is a block diagram of a structure of a communication unit of  FIG. 2 , according to an exemplary embodiment; 
         FIG. 4  illustrates an example of an operation in which the X-ray apparatus of  FIG. 1  images an object, according to an exemplary embodiment; 
         FIG. 5  illustrates a relationship between measured data and an image; 
         FIGS. 6A, 6B, and 6C  illustrate examples of truncations; 
         FIGS. 7A and 7B  illustrate examples in which an X-ray apparatus according to an exemplary embodiment images an object with a high radiation dose or a low radiation dose; 
         FIG. 8  is a block diagram of a structure of a medical imaging apparatus according to an exemplary embodiment; 
         FIG. 9  is a flowchart of a method of operating a medical imaging apparatus according to an exemplary embodiment; 
         FIG. 10  is a flowchart of a method of operating a medical imaging apparatus according to another exemplary embodiment; 
         FIG. 11  is a block diagram of a process of acquiring a reconstructed image from data measured by a medical imaging apparatus, according to an exemplary embodiment; 
         FIG. 12  is a flowchart of a process in which a medical imaging apparatus according to an exemplary embodiment acquires an estimated image through iterative reconstruction from measured data; 
         FIG. 13  illustrates an example of measured data and an initial image acquired according to an exemplary embodiment; 
         FIG. 14  illustrates an example of ROI-outside measured data and an ROI-outside image acquired according to an exemplary embodiment; 
         FIG. 15  illustrates an example of ROI-inside measured data and an ROI-inside image acquired according to an exemplary embodiment; 
         FIG. 16  illustrates a case of acquiring a reconstructed image from measured data by an iterative reconstruction technique according to an exemplary embodiment; 
         FIG. 17  illustrates a process of acquiring a reconstructed image from the measured data, according to an exemplary embodiment; 
         FIGS. 18A to 18D  are examples of the reconstructed images; 
         FIGS. 19A and 19B  are graphs showing the quality of reconstructed images variously acquired from truncated measured data; 
         FIG. 20  is a flowchart of a method of a method of operating a medical imaging apparatus according to an exemplary embodiment; 
         FIG. 21  is a block diagram of a process in which a medical imaging apparatus acquires a reconstructed image from the measured data, according to an exemplary embodiment; 
         FIGS. 22 to 24  are block diagrams of structures of medical imaging apparatuses according to exemplary embodiments; 
         FIG. 25  is a flowchart of a method of operating a medical imaging apparatus according to an exemplary embodiment; 
         FIG. 26  is a block diagram of a structure of an X-ray apparatus according to an exemplary embodiment; 
         FIG. 27  is a schematic view of a CT apparatus to which an exemplary embodiment is applicable; and 
         FIG. 28  is a block diagram of a structure of a CT apparatus according to an exemplary embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. Expressions such as “at least one of,” when preceding a list of elements, modify the entire list of elements and do not modify the individual elements of the list. 
     Hereinafter, the present disclosure will be described more fully with reference to the accompanying drawings where exemplary embodiments of the disclosure are shown. However, this disclosure may be embodied in many different forms and should not be construed as being limited only to the exemplary embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to one of ordinary skill in the art. Sizes of components in the drawings may be exaggerated for convenience of explanation. For example, since sizes and thicknesses of components in the drawings are illustrated for convenience of explanation, the embodiments of this disclosure are not limited by the drawings. 
     The terms used in the present disclosure have been selected from currently widely used general terms in consideration of the functions in the present disclosure. All terms including descriptive or technical terms used herein should be construed as having meanings that are obvious to one of ordinary skill in the art. When a term has an ambiguous meaning due to evolving of language, precedent cases, or appearance of new technologies, the meaning of a term used in this disclosure should first be clarified by its usage and/or definition in this disclosure. If the term cannot be clarified that way, then it should then be clarified as one of ordinary skill in the art would have understood the term at the time of this disclosure. 
     When a part “includes” or “comprises” an element, unless specified otherwise, it should be construed that the part can include at least one other element. Terms such as “˜portion,” “˜unit,” “˜module,” and “˜block” in the disclosure may signify a unit to process at least one function or operation and the unit may be embodied by hardware such as a field-programmable gate array (FPGA) or an application-specific integrated circuit (ASIC), software, or a combination of hardware and software. However, the unit may be configured to be located in a storage unit medium to be addressed or configured to be able to operate one or more processors. Accordingly, the unit as an example includes constituent elements such as software constituent elements, object-oriented software constituent elements, class constituent elements, and task constituent elements, processes, functions, attributes, procedures, sub-routines, segments of program codes, drivers, firmware, microcodes, circuits, data, databases, data structures, tables, arrays, and variables. The constituent elements and functions provided by the “units” may be combined into a smaller number of constituent elements and units or may be further divided into additional constituent elements and units. Accordingly, the present disclosure is not limited by a specific combination of hardware and software. 
     In the present specification, an “image” may signify multi-dimensional data formed of discrete image elements, for example, pixels in a two-dimensional (2D) image and voxels in a three-dimensional (3D) image. For example, an image may include an X-ray, a computed tomography (CT) image, a magnetic resonance imaging (MRI) image, an ultrasound image, and a medical image of an object acquired by other medical imaging apparatuses. 
     Also, in the present specification, an “object” may include a human, an animal, or a part of a human or an animal. For example, an object may include body parts such as liver, heart, womb, brain, breast, abdomen, blood vessels, etc. Also, an object may include a phantom that signifies matter having a volume that is approximately the intensity and effective atomic number of a living thing, and may include a sphere phantom having a property similar to a human body. 
     Also, in the present specification, a “user” may be a doctor, a nurse, a clinical pathologist, a medical imaging expert, a technician who fixes a medical apparatus, etc., but the present disclosure is not limited thereto. 
       FIG. 1  illustrates an X-ray apparatus  100  according to an exemplary embodiment. 
     Referring to  FIG. 1 , the X-ray apparatus  100  may include a C-arm  102  having a C shape and may be able to continuously perform X-ray imaging for a predetermined time period. An X-ray source  106  may be provided at one end of the C-arm  102  and a detector  108  may be provided at the other end of the C-arm  102 . The positions of the X-ray source  106  and the detector  108  on the C-arm  102  may be adjustable. Although it is not illustrated in  FIG. 1 , the C-arm  102  may be coupled to a ceiling, a floor, or both of the ceiling and the floor. Also, the X-ray apparatus  100  may further include a table  105  where an object  10  may be located. 
     The X-ray source  106  is configured to generate and transmit an X-ray. The detector  108  is configured to detect the X-ray that is transmitted by the X-ray source  106  through the object  10 . A medical image may be acquired based on the X-ray detected by the detector  108 . The C-arm  102  may rotate while the X-ray source  106  transmits X-ray. The detector  108  that rotates together with the X-ray source  106  may detect the X-ray that has transmitted through the object  10 . 
     As a user adjusts a position of at least one of the C-arm  102  and the table  105 , the object  10  may be imaged at various positions or various angles. For example, while a user rotates or moves the C-arm  102  and the table  105 , the object  10  may be imaged to acquire medical images. Accordingly, the user may more efficiently image the object  10  using the X-ray apparatus  100  for a continuous time period, compared to a general fixed type X-ray apparatus. 
     The X-ray apparatus  100  may be used for fluoroscopy where a plurality of X-ray images or an X-ray motion picture is to be acquired for a continuous time period. For example, the X-ray apparatus  100  may be useful in medical treatments such as X-ray angiography or surgical operation. When a medical doctor needs to carefully examine a patient with vascular disease to diagnose a disease, the medical doctor continuously performs X-ray imaging during an examination time. Then, a state of blood vessels of a patient is examined through fluoroscopy, which uses X-rays to acquire real time moving images. 
     Accordingly, in a medical treatment such as angiography, X-ray is continuously transmitted toward the object  10  during treatment time to acquire fluoroscopic images. For example, X-ray imaging may allow a user, who may be a medical doctor, to see his progress when he is installing a guide wire around an object. Or, the X-ray imaging may allow the doctor to see where he is injecting a drug using a thin needle or a catheter. 
     During surgery, the doctor may insert a catheter, stent, or an injection needle into a human body. Accordingly, the user may perform the procedure by acquiring fluoroscopic images to check the position of a target object such as a catheter during the treatment. Accordingly, the user may be able to check whether the catheter is accurately inserted in a target position of the object  10 . 
     The X-ray apparatus may be, for example, an interventional X-ray apparatus, interventional angiography C-arm X-ray apparatus, or a surgical C-arm X-ray apparatus. 
       FIG. 2  illustrates a structure of the X-ray apparatus  100  of  FIG. 1 . 
     Referring to  FIG. 2 , the X-ray apparatus  100  may include the X-ray source  106 , the detector  108 , and the C-arm  102  connecting the X-ray source  106  and the detector  108 . Also, the X-ray apparatus  100  may further include a rotation driver  110 , a data acquisition circuit  116 , a data transmission unit  120 , the table  105 , a controller  118 , a storage unit  124 , an image processor  126 , an input unit  128 , a display  130 , a communication unit  132 . 
     The object  10  may be located on the table  105 . The table  105  according to an exemplary embodiment may move in predetermined directions such as, for example, up, down, left, right, etc., and the motion of the table  105  may be controlled by the controller  118 . 
     The X-ray source  106  and the detector  108  connected to the C-arm  102  to face each other have a predetermined field of view (FOV). When the X-ray source  106  and the detector  108  are rotated as the C-arm  102  rotates, the FOV may be changed accordingly. 
     X-ray radiation arriving at the detector  108  may include not only attenuated primary radiation forming a useful image, but also scattered radiation degrading the quality of an image. An anti-scatter grid  114  may be located on the detector  108  between a patient and the detector  108  (or a photosensitive film) in order to facilitate transmission of most of the primary radiation and attenuate the scattered radiation. 
     For example, the anti-scatter grid  114  may be configured in the form of alternately stacking strips of lead foil, a solid polymer material or solid polymer, and an interspace material such as a fiber composite material. However, the configuration of the anti-scatter grid  114  is not necessarily limited to this specific configuration. 
     The C-arm  102  may receive a drive signal and power from the rotation driver  110 , and rotate the X-ray source  106  and the detector  108  at a predetermined rotation speed. The X-ray source  106  may generate and transmit an X-ray by receiving a voltage and current from a power distribution unit (PDU, not shown) through a high voltage generator (not shown). When the high voltage generator applies a predetermined tube voltage to the X-ray source  106 , the X-ray source  106  may generate X-rays having a plurality of energy spectrums corresponding to the tube voltage. X-rays generated by the X-ray source  106  may be transmitted in a predetermined shape by a collimator  112 . 
     The detector  108  may be located facing the X-ray source  106 . The detector  108  may include a plurality of X-ray detection elements. A single X-ray detection element may form a single channel, but not limited thereto. 
     The detector  108  may detect the X-ray from the X-ray source  106  that is transmitted through the object  10  and generate an electrical signal corresponding to the intensity of the detected X-ray. 
     The detector  108  may include an indirect type detector that detects radiation by converting the radiation to light or a direct type detector that detect radiation by directly converting the radiation to electric charges. The indirect type detector may use a scintillator. The direct type detector may use a photon counting detector. 
     The data acquisition circuit  116  may be connected to the detector  108 . The electrical signal generated by the detector  108  may be collected by the data acquisition circuit  116  wirelessly or via wire. Also, the electrical signal generated by the detector  108  may be provided to an analog-to-digital converter (not shown) through an amplifier (not shown) to form digital data. 
     Depending on the thickness and/or number of slices of the images, only part of digital data collected by the detector  108  may be provided to the image processor  126 . Or the image processor  126  may select the data it may choose to use. The data transmission unit  120  may transmit the digital data to the image processor  126  wirelessly or via wire. 
     The controller  118  according to an exemplary embodiment may control operation of each of the modules in the X-ray apparatus  100 . For example, the controller  118  may control operation of the table  105 , the rotation driver  110 , the collimator  112 , the data acquisition circuit  116 , the storage unit  124 , the image processor  126 , the input unit  128 , the display  130 , and the communication unit  132 . 
     The image processor  126  may receive the digital data acquired from the data acquisition circuit  116 , which may be, for example, raw data before processing, and perform pre-processing on the digital data. 
     The pre-processing may include, for example, a process of correcting irregular sensitivity between channels or a process of correcting signal loss due to radical decrease of signal intensity or an X-ray absorption material such as metal. 
     The pre-processed data by the image processor  126  may be referred to as projection data. The projection data may be stored in the storage unit  124  with its associated imaging parameters for data acquisition, for example, the tube voltage, imaging angle, etc. 
     The projection data may be a set of data values corresponding to the intensity of an X-ray transmitting through the object  10 . For convenience of explanation, a set of the projection data simultaneously acquired at the same imaging angle with respect to all channels is referred to as a projection data set or measured data. 
     The storage unit  124  may include at least one type of storage unit media including flash memory, hard disk, multimedia card, card type memory such as SD or XD, random access memory (RAM), static RAM (SRAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), programmable ROM (PROM), magnetic memory, magnetic disc, optical disc, etc. 
     Also, the image processor  126  may acquire a reconstructed image of the object  10  based on the measured data, where the reconstructed image may be three-dimensional (3D). The image processor  126  may generate a 3D image of the object  10  based on the acquired measured data using, for example, a cone beam reconstruction method. 
     The input unit  128  may receive an external input such as image processing conditions for X-ray tomography. For example, the X-ray tomography conditions may include setting a plurality of tube voltages and a plurality of energy values of X-rays, selecting an imaging protocol, selecting an image reconstruction method, setting an FOV area, setting an ROI area, setting the number of slices and slice thickness, and image post-processing parameters. Also the image processing conditions may include setting the resolution of an image, setting an attenuation coefficient of an image, and setting a combination ratio of an image. 
     The input unit  128  may include a device to receive input from the outside. For example, the input unit  128  may include a microphone, a keyboard, a mouse, a joystick, a touch pad, a touch pen, and a voice and gesture recognition device. 
     The display  130  may display an image reconstructed by the image processor  126 . 
     The transmission and receiving of data or power between the above-described elements may be performed by using at least one of wired, wireless, and optical communication methods. 
     The communication unit  132  may communicate with an external device or an external medical apparatus via a server  134 . Alternatively, the X-ray apparatus  100  may connect through the communication unit  132  to a workstation (not shown) that is configured to control the X-ray apparatus  100 . This will be described with reference to  FIG. 3 . 
       FIG. 3  is a block diagram of a structure of the communication unit  132  of  FIG. 2 , according to an exemplary embodiment. 
     The communication unit  132  may be connected to a network  15  wirelessly or via a wired connection and may communicate with an external device such as the server  134 , a medical apparatus  136 , a portable apparatus  138 , or a workstation  139 . The communication unit  132  may exchange data with a hospital sever or other medical apparatuses in a hospital through a medical image information system such as, for example, picture archiving and communication system (PACS). 
     Also, the communication unit  132  may perform data communication with the portable apparatus  138  using digital imaging and communications in medicine (DICOM), which is a medical digital imaging and communication standard. 
     The communication unit  132  may transmit and receive data related to the diagnosis of the object  10  via the network  15 . Also, the communication unit  132  may transmit or receive a medical image acquired by the medical apparatus  136 , which may be, for example, an MRI apparatus or an X-ray apparatus. 
     Furthermore, the communication unit  132  may receive information about a diagnosis history or treatment schedule of a patient from the server  134  and use the received information for clinical diagnosis of a patient. Also, the communication unit  132  may perform data communication not only with the server  134  or the medical apparatus  136  in a hospital, but also with the portable apparatus  138  of a user or a patient, and with the workstation  139 . 
     Also, the communication unit  132  may transmit information about a status of equipment and a status of quality management to a system manager or a service manager via a network, and receive feedback thereon. 
     The workstation  139  may be in a separate area from the X-ray apparatus  100 . For example, the X-ray apparatus  100  may be in a shield room and the workstation  139  may be in a console room. A shield room may be where the object  10  is imaged, and may also be variously referred to as the “imaging room,” the “examination laboratory,” or the “examination room.” A user may control the X-ray apparatus  100  from a console room. The console room and the shield room may be separated from each other by a shielding wall to protect a user from a magnetic field, radiation, or a radio frequency (RF) signal transmitted from the shield room. 
       FIG. 4  illustrates an example of an operation in which the X-ray apparatus  100  of  FIG. 1  images the object  10 , according to an exemplary embodiment. In  FIG. 4 , for convenience of explanation, only the X-ray source  106  and the detector  108  are illustrated among the elements of the X-ray apparatus  100  of  FIG. 1 . 
     Referring to  FIGS. 1 and 4 , the X-ray source  106  and the detector  108 , connected to each other by the C-arm  102 , may rotate around the object  10 . The X-ray source  106  transmits an X-ray to the object  10 , and the detector  108  detects the X-ray that passes through the object  10 . The X-ray source  106  and the detector  108  arranged facing each other have a predetermined FOV. When the X-ray source  106  and the detector  108  rotate, the FOV may be changed accordingly. For example, when the X-ray source  106  is located at position P 1 , the detector  108  is located at a position facing the position P 1  and has a field of view FOV- 1  corresponding to the position P 1 . Also, when the X-ray source  106  is located at position P 2 , the detector  108  is located at a position facing the position P 2  and has a field of view FOV- 2  corresponding to the position P 2 . 
     The X-ray source  106  is moved by a predetermined rotation angle to change positions, for example, to P 1  or P 2 , and transmits an X-ray. The detector  108  detects the X-ray transmitted at each position, for example, P 1  or P 2 , of the X-ray source  106  to acquire projection data. The projection data may be a set of signal values corresponding to the intensity of the X-ray detected by the detector  108 . 
     In detail, when the X-ray source  106  is located at position P 1 , the detector  108  may acquire first raw data by detecting the X-ray transmitted toward the object  10 . Also, when the X-ray source  106  is located at position P 2 , the detector  108  may acquire second raw data by detecting the X-ray transmitted toward the object  10 . Accordingly, the X-ray apparatus  100  may acquire a plurality of projection data corresponding to the raw data from the respective positions of the X-ray source  106 . The X-ray apparatus  100  may acquire one measured data by combining a plurality of projection data. The measured data may be referred to as the sinogram. The X-ray apparatus  100  may acquire a reconstructed image by imaging a ROI from the measured data. The ROI is an area that may be reconstructed by the X-ray apparatus  100  to an image. 
       FIG. 5  illustrates a relationship between the measured data and an image. 
     Referring to  FIG. 5 , measured data  40  may be generated by combining a plurality of pieces of projection data acquired as the detector  108  detects the X-ray transmitted by the X-ray source  106  that rotates about the object  10 , as illustrated in  FIG. 4 . 
     The image  50  may be acquired by back-projecting the measured data  40 . Also, the measured data  40  may be acquired by re-projecting the image  50 . 
     A technique to acquire the image  50  by back-projecting the measured data  40  is referred to as the analytical reconstruction technique. The analytical reconstruction technique may include a filtered back-projection (FBP) based reconstruction technique to acquire the image  50  by filtering and back-projecting the measured data  40 , and a back-projection and filtration (BPF) technique to acquire the image  50  by back-projecting and filtering the measured data  40 . 
     Referring back to  FIG. 4 , when the X-ray apparatus  100  of  FIG. 1  images the object  10 , that is, while the X-ray source  106  and the detector  108  rotate, the object  10  is within an FOV, for example, FOV- 1  or FOV- 2 . However, while the X-ray source  106  and the detector  108  rotate, if a part of the object  10  is not within an FOV, truncation may be generated. 
       FIGS. 6A, 6B, and 6C  illustrate examples of truncations. In  FIG. 6 , for convenience of explanation, only the X-ray source  106  and the detector  108  of the elements included in the X-ray apparatus  100  of  FIG. 1  are illustrated. 
     Referring to  FIGS. 6A, 6B, and 6C , when the size of the object  10  is too big ( FIG. 6A ), the size of the detector  108  is too small ( FIG. 6B ), or a distance DSO between the X-ray source  106  and the object  10  is too short, truncation may be generated. The truncation generated in the cases of  FIGS. 6A, 6B, and 6C  may cause an artifact in an image acquired from the measured data, thereby deteriorating the quality of the image. Accordingly, various embodiments of the present disclosure describe image reconstruction methods that may reduce artifact due to truncation during acquisition of an image. 
     In addition to the truncation, a low radiation dose may also deteriorate the quality of an image. According to an exemplary embodiment, the X-ray apparatus  100  of  FIG. 1  performs X-ray imaging while the C-arm  102  rotates. Accordingly, as imaging time increases the total X-ray dosage transmitted to the object  10  increases as well. However, since X-ray is radiation that can be harmful to a human body, a user needs to minimize an X-ray dose the object  10  is exposed to during the X-ray imaging. Accordingly, the X-ray apparatus  100  according to an exemplary embodiment may image the object  10  with a low radiation dose. 
       FIGS. 7A and 7B  illustrate examples where the X-ray apparatus  100  according to an exemplary embodiment images the object  10  with a high radiation dose or a low radiation dose. In  FIG. 7 , for convenience of explanation, only the X-ray source  106  of the X-ray apparatus  100  of  FIG. 1  is illustrated. 
     A rotation angle at which the position of the X-ray source  106  in  FIG. 7A  is changed is smaller than a rotation angle of the X-ray source  106  in  FIG. 7B . Accordingly, in  FIG. 7A , the X-ray apparatus  100  may image the object  10  with a higher total radiation dose compared to the case of  FIG. 7B . For example, when the rotation angle of  FIG. 7B  is twice the rotation angle of  FIG. 7A , the X-ray apparatus  100  of  FIG. 7B  may image the object  10  with a total X-ray dose that is 50% of that of  FIG. 7A . Also, when the X-ray apparatus  100  of  FIG. 7A  images the object  10  by full sampling, the X-ray apparatus  100  of  FIG. 7B  is said to image the object  10  by undersampling. 
     Whether the total dose of X-rays transmitted by the X-ray apparatus  100  to image the object  10  is a high radiation dose or a low radiation dose may be determined by the rotation angle of the X-ray source  106 . When the rotation angle of the X-ray source  106  is greater than a preset degree “n,” the X-ray dose may be regarded as a low radiation dose. For example, the degree “n” may be 1°. In other words, when the X-ray source  106  transmits an X-ray to create an image by rotating at an angle greater than 1°, the X-ray dose may be regarded as a low radiation dose. However, this is merely exemplary and the rotation angle to determine whether the X-ray dose is a low radiation dose or not may be different according to the characteristics of the X-ray apparatus  100  such as the distance between the X-ray source  106  and the detector  108  of  FIG. 1  or the size of the detector  108  of  FIG. 1 . 
     However, when the object  10  is imaged with a low radiation dose as in  FIG. 7B , compared to the case of  FIG. 7A , the number of projection data acquired by the X-ray apparatus  100  decreases. Accordingly, as incomplete measured data is acquired, a low radiation dose distortion phenomenon may occur that may lead to deteriorated quality of a reconstructed image. 
     Accordingly, when truncation is generated as in  FIG. 6  or the X-ray apparatus  100  of  FIG. 1  images the object  10  with a low radiation dose as in  FIG. 7B , an image reconstruction method capable of preventing deterioration of image quality may be desired. In the following description, a medical imaging apparatus and a medical imaging method according to an exemplary embodiment that may address the issues of truncation and a low radiation dose are described. 
       FIG. 8  is a block diagram of a structure of a medical imaging apparatus  300  according to an exemplary embodiment. Referring to  FIG. 8 , the medical imaging apparatus  300  may include a data acquirer  310  and an image processor  320 . 
     The data acquirer  310  may acquire measured data by performing X-ray imaging on an object. The measured data may be at least one of truncated data and data acquired with a low radiation dose smaller than a preset reference value. The measured data may be truncated data acquired under a truncation environment as illustrated in  FIGS. 6A, 6B, and 6C . Alternatively, the measured data may be acquired by imaging the object with a low radiation dose as illustrated in  FIG. 7B . As described in  FIG. 7B , when the rotation angle of the X-ray source  106  is greater than a preset angle, the X-ray dose may be considered as a low radiation dose. The image processor  320  may generate a reconstruction image based on the measured data. 
     The medical imaging apparatus  300  may be included in the X-ray apparatus  100  of  FIGS. 1 and 2 . When the medical imaging apparatus  300  is included in the X-ray apparatus  100  of  FIG. 2 , the data acquirer  310  may correspond to at least one of the detector  108 , the data acquisition circuit  116 , and the data transmission unit  120 . Also, the image processor  320  may correspond to the image processor  126  of  FIG. 2 . In this case, all the above specified elements may be included in the medical imaging apparatus  300  of  FIG. 8 . 
     Alternatively, the medical imaging apparatus  300  may be included in the server  134 , the medical apparatus  136 , the portable apparatus  138 , or the workstation  139  of  FIG. 3 , which is connected to the X-ray apparatus  100  of  FIG. 1  via a network. In this case, the data acquirer  310  of the medical imaging apparatus  300  may receive the measured data transmitted by the communication unit  132  of the X-ray apparatus  100  of  FIG. 2  via the network  15  of  FIG. 3 . 
     A method in which the image processor  320  generates a reconstructed image, according to an exemplary embodiment, is described below. 
       FIG. 9  is a flowchart of a method (S 100 ) of operating a medical imaging apparatus according to an exemplary embodiment. 
     Referring to  FIG. 9 , the medical imaging apparatus may acquire measured data (S 110 ). The medical imaging apparatus may acquire an initial image based on the measured data (S 120 ). For example, an initial image may be the reconstructed image as described with reference to  FIGS. 2, 4, 9, 10, 11, and 13-17 . Additionally, an initial image may be formed by removing an outside of a ROI from a reconstructed image. 
     The medical imaging apparatus may alternately estimate ROI-outside measured data and ROI-inside measured data based on the measured data and the initial image (S 130 ). The ROI-outside measured data may be an estimated difference between data acquired by re-projecting an inside of an ROI in the initial image and the measured data. The ROI-inside measured data may be an estimated difference between data acquired by re-projecting the ROI-outside image and the measured data. 
     In various embodiments of the present disclosure, either of the ROI-outside measured data or the ROI-inside measured data may be estimated first. 
     For example, the medical imaging apparatus may first estimate the ROI-outside measured data based on the measured data and the initial image. Next, the medical imaging apparatus may estimate the ROI-inside measured data based on a difference between the measured data and the ROI-outside measured data. 
     In another example, the medical imaging apparatus may first estimate ROI-inside measured data based on the measured data and the initial image. In this case, the medical imaging apparatus may estimate the ROI-outside measured data based on a difference between the measured data and the ROI-inside measured data. Next, the ROI-inside measured data may be updated based on the estimated ROI-outside measured data. 
     The medical imaging apparatus may acquire a reconstructed image based on the ROI-inside measured data (S 140 ). 
     As such, the medical imaging apparatus according to an exemplary embodiment may acquire the ROI-inside measured data that is a result of removing influence of incomplete data about the outside of ROI from the measured data by removing the estimated ROI-outside measured data from the measured data. The reconstructed image acquired based on the ROI-inside measured data may have better image quality than the initial image acquired based on the measured data. 
       FIG. 10  is a flowchart of a method (S 200 ) of operating a medical imaging apparatus according to another exemplary embodiment. 
     Referring to  FIG. 10 , the medical imaging apparatus may acquire measured data (S 210 ). The medical imaging apparatus may acquire an initial image based on the measured data (S 220 ). 
     The medical imaging apparatus may estimate ROI-outside measured data based on the measured data and the initial image (S 230 ). The medical imaging apparatus may estimate ROI-inside measured data based on a difference between the measured data and the ROI-outside measured data (S 240 ). 
     The medical imaging apparatus may determine whether to update the ROI-outside measured data and the ROI-inside measured data (S 250 ). When it is determined to update, the medical imaging apparatus updates the estimated ROI-outside measured data and the estimated ROI-inside measured data by re-performing operations S 230  and S 240 . 
     The medical imaging apparatus may perform an update operation including updating the ROI-outside measured data and the ROI-inside measured data by repeatedly performing operations S 230 , S 240 , and S 250  until it is determined to stop updating in operation S 250 . 
     When the update operation is stopped, the medical imaging apparatus may acquire a reconstructed image based on a finally estimated ROI-inside measured data (S 260 ). In other words, the medical imaging apparatus may acquire a reconstructed image based on a finally updated ROI-inside measured data. 
     A condition for determining whether to update may be set in various ways. For example, after repeating the operations S 230  to S 250  by a predetermined update repetition number, the update operation may be stopped. The repetition number may be initially determined as a default. Next, the repetition number may be adjusted by a user or determined based on the characteristics of the object or the characteristics of the measured data. However, the present disclosure is not limited thereto and other stopping conditions are described with reference to other drawings. 
     The methods S 100  and S 200  of operating a medical imaging apparatus of  FIGS. 9 and 10  may be performed by the medical imaging apparatus  300  of  FIG. 8 . For example, the image processor  320  of the medical imaging apparatus  300  of  FIG. 8  may perform the methods of S 100  and S 200 . Alternatively, the methods S 100  and S 200  of operating a medical imaging apparatus of  FIGS. 9 and 10  may be performed by the X-ray apparatus  100  of  FIG. 2 . For example, the image processor  126  of the X-ray apparatus  100  of  FIG. 2  may perform the methods of S 100  and S 200 . Alternatively, the methods S 100  and S 200  of operating a medical imaging apparatus may be performed by the server  134 , the medical apparatus  136 , the portable apparatus  138 , or the workstation  139  of  FIG. 3 . Accordingly, all the above descriptions may be applied to the methods S 100  and S 200  of operating a medical imaging apparatus of  FIGS. 9 and 10 . 
     As such, according to an exemplary embodiment, ROI-outside measured data and ROI-inside measured data may be alternately estimated. The ROI-outside measured data and the ROI-inside measured data may be independently estimated. Also, accuracy of the estimated ROI-inside measured data may be improved by repeatedly performing alternate estimation of the ROI-outside measured data and the ROI-inside measured data. As the accuracy of the estimated ROI-inside measured data increases, the quality of a reconstructed ROI-inside image may increase as well. 
       FIG. 11  is a block diagram of a process of acquiring a reconstructed image from data measured by a medical imaging apparatus, according to an exemplary embodiment. 
     Referring to  FIG. 11 , a medical imaging apparatus may acquire an initial image  71  by reconstructing measured data  70  (S 21 ). The medical imaging apparatus may acquire the initial image  71  by the analytical reconstruction technique described with reference to  FIG. 5 . Alternatively, the medical imaging apparatus may acquire the initial image  71  from the measured data  70  by an iterative reconstruction technique described with reference to  FIG. 12 . The iterative reconstruction technique may be a compressed sensing based iterative reconstruction technique. Also, when the initial image  71  is acquired by reconstructing the measured data  70 , the medical imaging apparatus may apply extrapolation based truncation correction together with the reconstruction techniques. 
     The initial image  71  may be an image acquired by removing the outside of ROI from an image acquired by reconstructing the measured data  70  (S 21 ), leaving the inside of the ROI only. For example, in the image acquired by reconstructing the measured data  70  (S 21 ), by processing pixel values of pixels included in the outside of the ROI as “0,” the initial image  71  where the outside of the ROI is removed may be acquired. 
     The medical imaging apparatus may re-project (RP) the inside of the ROI in the initial image  71  to acquire ROI-inside RP data  72 . The medical imaging apparatus may acquire the ROI-inside RP data  72  by re-projecting only the inside of the ROI in the initial image  71 . When the initial image  71  is an image where the outside of ROI is removed, the medical imaging apparatus may acquire the ROI-inside RP data  72  by re-projecting the initial image  71 . The re-projecting may be performed in various ways, for example, ray-driven, voxel-driven, or distance-driven. 
     The medical imaging apparatus may estimate a difference between the measured data  70  and the ROI-inside RP data  72  that is data acquired by re-projecting the inside of ROI in the initial image  71 , as ROI-outside measured data  73  (S 22 ). The measured data  70  may include both of data about the inside of ROI and data about the outside of ROI. However, since the ROI-inside RP data  72  is data acquired by re-projecting the inside of ROI of the initial image  71 , the ROI-outside measured data  73  acquired by removing the ROI-inside RP data  72  from the measured data  70  may be estimated as data about the outside of ROI of the measured data  70 . 
     The medical imaging apparatus may acquire an ROI-outside image  74  by reconstructing the estimated ROI-outside measured data  73  (S 23 ). The medical imaging apparatus may acquire the ROI-outside image  74  based on the ROI-outside measured data  73  using the iterative reconstruction technique. The medical imaging apparatus may acquire the ROI-outside image  74  by removing the inside of ROI from an image acquired based on the ROI-outside measured data  73  using the iterative reconstruction technique, leaving the outside of ROI only. 
     The medical imaging apparatus may acquire ROI-outside RP data  75  by re-projecting the ROI-outside image  74 . The medical imaging apparatus may estimate ROI-inside measured data  76  as a difference between the ROI-outside RP data  75  and the measured data  70  (S 24 ). 
     The medical imaging apparatus may acquire ROI-inside image  77  by reconstructing the estimated ROI-inside measured data  76  (S 25 ). The medical imaging apparatus may acquire the ROI-inside image  77  based on the ROI-inside measured data  76  using the iterative reconstruction technique. The medical imaging apparatus may acquire the ROI-inside image  77  by removing the outside of ROI from an image acquired based on the ROI-inside measured data  76  using the iterative reconstruction technique, leaving the inside of ROI only. 
     The medical imaging apparatus may determine whether to update the ROI-outside measured data  73  and the ROI-inside measured data  76  (S 26 ). 
     When it is determined to update further, the medical imaging apparatus updates the ROI-outside measured data  73  based on the ROI-inside image  77 , not the initial image  71 . Hence, the ROI-inside measured data  76  is updated based on the updated ROI-outside measured data  73 , and the ROI-inside image  77  is updated based on the updated ROI-inside measured data  76 . 
     In detail, the updated ROI-inside RP data  72  may be acquired by re-projecting the inside of the ROI in the ROI-inside image  77 . There may be a difference between the ROI-inside RP data  72  acquired by re-projecting the initial image  71  before update and the ROI-inside RP data  72  acquired by re-projecting the ROI-inside image  77 . The medical imaging apparatus may update the ROI-outside measured data by re-estimating the difference between the ROI-inside RP data  72  acquired by re-projecting the inside of ROI in the ROI-inside image  77  and the measured data  70  as the ROI-outside measured data (re-performing operation S 22 ). 
     The medical imaging apparatus may acquire the updated ROI-outside image  74  by reconstructing the updated ROI-outside measured data  73  (re-performing operation S 23 ). The medical imaging apparatus may update the ROI-inside measured data  76  by re-estimating a difference between the ROI-outside RP data  75 , acquired by re-projecting the updated ROI-outside image  74 , and the measured data  70  as the ROI-inside measured data  76  (re-performing operation S 24 ). 
     The medical imaging apparatus may acquire the updated ROI-inside image  77  by reconstructing the updated ROI-inside measured data  76  (re-performing operation S 25 ). The medical imaging apparatus may determine again whether to update (re-performing operation S 26 ). 
     As such, the medical imaging apparatus may iteratively perform the operations S 22 , S 23 , S 24 , S 25 , and S 26  until a determination is made to stop updating in operation S 26 . Thus, the update operations including updating the ROI-outside measured data  73 , updating the ROI-inside measured data  76 , and updating the ROI-inside image  77  may be iteratively performed. 
     When it is determined to stop updating in operation S 26 , the medical imaging apparatus may acquire a reconstructed image  78  based on the finally updated ROI-inside image  77 . The reconstructed image  78  may be the finally updated ROI-inside image  77 . 
     Conditions for determining whether to update may be set in various ways. For example, the update operation may be stopped after a predetermined number of updates. For example, the predetermined update repetition number may be two or more. However, the present disclosure is not limited thereto. Alternatively, the update operation may be stopped when a difference between the updated ROI-inside measured data  76  and the update acquired by re-projecting the ROI-inside image  77  is equal to or less than a predetermined threshold value. The threshold value may be initially determined to be a default. The threshold value may also be adjusted by a user or determined based on the characteristics of the object or the characteristics of the measured data. However, the present disclosure is not limited thereto. For example, the threshold value may be set to an attenuation value having 6 decimal places (0.00000×). However, the present disclosure is not limited thereto. 
     Also, the user may determine whether to update after checking the ROI-inside image  77 . 
       FIG. 12  is a flowchart of a process S 10  in which a medical imaging apparatus according to an exemplary embodiment acquires an estimated image through iterative reconstruction from measured data. 
     The process S 10  of  FIG. 12  may be applied to operation S 21  of reconstructing the initial image  71  from the measured data  70  of  FIG. 11 , operation S 23  reconstructing the ROI-outside image  74  from the ROI-outside measured data  73 , and operation S 25  of reconstructing the ROI-inside image  77  from the ROI-inside measured data  76 . In other words, the measured data of  FIG. 12  may be the measured data  70 , the ROI-outside measured data  73 , or the ROI-inside measured data  76  in  FIG. 11 . The estimated image of  FIG. 12  may be the initial image  71 , the ROI-outside image  74 , or the ROI-inside image  77  according to the type of the measured data. 
     Referring to  FIG. 12 , the medical imaging apparatus may re-project an initial estimated image (S 11 ). The initial estimated image may be a default image. The initial estimated image may be an image in which all pixel values are constant. For example, the initial estimated image may be an image in which all pixel values are “0.” 
     The medical imaging apparatus may compare the data acquired by re-projecting the initial estimated image and the measured data, and acquire a difference value therebetween (S 12 ). The medical imaging apparatus may back-project the difference value (S 13 ). The medical imaging apparatus may acquire an updated estimated image by overlapping an image acquired by re-projecting the difference value on the initial estimated image (S 14 ). 
     The medical imaging apparatus may determine whether to stop the iterative reconstruction process (S 15 ). For example, when the difference value acquired in the operation S 12  is equal to or less than a predetermined threshold value, the iterative reconstruction process may be stopped. For example, the threshold value may be set to an attenuation value having 6 decimal places (0.00000×). However, the present disclosure is not limited thereto and the threshold value may be set in various ways according to the quality of an image that the user wants or the characteristics of the object. 
     Unless the iterative reconstruction process is stopped, the medical imaging apparatus re-performs re-projecting the estimated image updated in the operation S 14  (S 11 ), acquiring a difference value by comparing the data acquired by re-projecting the updated estimated image and the measured data (S 12 ), back-projecting the difference value (S 13 ), and updating again the estimated image by overlapping the image acquired by back-projecting the difference on the updated estimated image (S 14 ). Next, the medical imaging apparatus may determine again whether to stop the iterative reconstruction process (S 15 ). 
     When the iterative reconstruction process is stopped, the medical imaging apparatus may determine the finally updated estimated image to be an estimated image. The medical imaging apparatus may further perform post-filtering such as TV minimization or soft thresholding on the estimated image. 
     Next, referring to  FIGS. 13 to 15 , according to an exemplary embodiment, the data and image acquired from a process of acquiring a reconstructed image from the measured data. 
       FIG. 13  illustrates an example of measured data  80  and an initial image  81  acquired according to an exemplary embodiment. 
     Referring to  FIG. 13 , the medical imaging apparatus may acquire the initial image  81  by reconstructing the measured data  80 . The measured data  80  is an example of the measured data  70  of  FIG. 11  and the initial image  81  is an example of the initial image  71  of  FIG. 11 . 
     It may be seen that the quality of the initial image  81  has many artifacts and is not good. The quality of the initial image  81  may be deteriorated due to truncation or a low radiation dose. 
       FIG. 14  illustrates an example of ROI-outside measured data  83  and an ROI-outside image  84  acquired according to an exemplary embodiment. 
     Referring to  FIG. 14 , the medical imaging apparatus may acquire the ROI-outside image  84  by reconstructing the ROI-outside measured data  83 . The ROI-outside measured data  83  is an example of the ROI-outside measured data  73  of  FIG. 11 , and the ROI-outside image  84  is an example of the ROI-outside image  74  of  FIG. 11 . 
       FIG. 15  illustrates an example of ROI-inside measured data  86  and an ROI-inside image  87  acquired according to an exemplary embodiment. 
     Referring to  FIG. 15 , the medical imaging apparatus may acquire the ROI-inside image  87  by reconstructing the ROI-inside measured data  86 . The ROI-inside measured data  86  is an example of the ROI-inside measured data  76  of  FIG. 11 , and the ROI-inside image  87  is an example of the ROI-inside image  77  of  FIG. 11 . 
     In comparison with  FIG. 13  and  FIG. 15 , compared to the initial image  81  of  FIG. 13  acquired by reconstructing the measured data  80 , the ROI-inside image  87  reconstructed based on the ROI-inside measured data  86  may have improved image quality as artifact is removed. 
       FIG. 16  illustrates a case of acquiring a reconstructed image from the measured data by an iterative reconstruction technique according to an exemplary embodiment. 
     In graph (a) of  FIG. 16 , the horizontal axis corresponds to the position of the detector  108  of  FIG. 4  and the vertical axis corresponds to the magnitude of data. The line g 510  is measured data and the line g 610  is data acquired by re-projecting an initial estimated image. As described in  FIG. 12 , as the initial estimated image may be iteratively updated so that the difference between the measured data (g 510 ) and the re-projected data (g 610 ) of the initial estimated image is minimized, thereby acquiring the estimated image. In  FIG. 16 , the estimated image that is iteratively updated may be a reconstructed image. 
     Graph (b) of  FIG. 16  illustrates a comparison between the measured data (g 510 ) and the re-projected data (g 620 ) of the reconstructed image. The difference between the re-projected data (g 620 ) of the reconstructed image acquired through iterative update and the measured data (g 510 ) may be greatly reduced, compared to the graph (a) of  FIG. 16 . 
     However, the re-projected data (g 620 ) of the reconstructed image is greater than the measured data (g 510 ) at a central portion of the detector but smaller than the measured data (g 510 ) at the edges of the detector. Such a non-linear offset is generated when the measured data is acquired in a truncation situation or by low-radiation dose imaging. When truncation is generated, the measured data includes data about both the inside of ROI and outside of ROI. In other words, since the iterative reconstruction does not consider or treat data about the outside of ROI, the non-linear offset may not be removed through the iterative reconstruction. Accordingly, the quality of a reconstructed image may be deteriorated and acquiring a high quality reconstructed image may be impossible. 
       FIG. 17  illustrates a process of acquiring a reconstructed image from the measured data, according to an exemplary embodiment. 
     In graph (a) of  FIG. 17 , the line g 310  denotes measured data, and the line g 410  denotes data acquired by re-projecting an initial image. According to an exemplary embodiment, the medical imaging apparatus may estimate ROI-outside measured data through a difference between the data acquired by re-projecting the initial image (g 410 ) and the measured data (g 310 ). Also, the ROI-inside measured data may be estimated based on the ROI-outside measured data. 
     In graph (b) of  FIG. 17 , the line g 320  denotes the ROI-inside measured data. In other words, the ROI-inside measured data (g 320 ) acquired by removing the ROI-outside measured data from the measured data (g 310 ) may be estimated. Next, a reconstructed image may be acquired from the ROI-inside measured data (g 320 ) through the iterative reconstruction technique. A reconstructed image may be acquired through the iterative reconstruction technique based on the ROI-inside measured data (g 320 ) and the initial image. 
     In graph (c) of  FIG. 17 , the line g 420  denotes re-projected data of the reconstructed image. When the ROI-inside measured data (g 320 ) and the re-projected data (g 420 ) of the reconstructed image are compared, it may be seen that the two pieces of data are almost matched with each other and non-linear offset is not generated, unlike graph (b) of  FIG. 16 . 
     As such, according to an exemplary embodiment, the ROI-inside measured data acquired by removing the effect of incomplete data about the outside of ROI from the measured data may be estimated, and the reconstructed image may be acquired from the ROI-inside measured data through the iterative reconstruction. In this case, the non-linear offset, which may be present in the reconstructed image acquired from the measured data, may be alleviated by iterative reconstruction and, thus, the quality of a reconstructed image may be improved. Also, according to an exemplary embodiment, a high quality image may be provided even when the object is imaged at a low radiation dose. Accordingly, the medical imaging apparatus that has high safety with respect to the object and has an improved user satisfaction may be provided. 
       FIGS. 18A to 18D  are examples of the reconstructed images.  FIG. 18A  is a ground truth image that is a reference for evaluating the quality of an image.  FIGS. 18B, 18C, and 18D  are images all acquired from the measured data acquired by imaging an object at a radiation dose of 50%.  FIG. 18B  is a reconstructed image acquired from the measured data through the analytical reconstruction technique.  FIG. 18C  is a reconstructed image acquired from the measured data through the iterative reconstruction technique.  FIG. 18D  is a reconstructed image acquired from the measured data according to an exemplary embodiment. Among  FIGS. 18B, 18C, and 18D , the image of  FIG. 18D  is closest to the ground truth image of  FIG. 18A . Also, it may be seen that artifacts due to truncation appearing on the image of  FIG. 18B  are not shown in the image of  FIG. 18D . In other words, it may be seen from the image of  FIG. 18D  that a low radiation dose distortion phenomenon may be improved and artifacts removed from a boundary of the inside and outside of ROI, that is, an adjacent area of truncation. As such, it may be seen from  FIGS. 18A to 18D  that the quality of the reconstructed images acquired according to an exemplary embodiment is remarkably improved compared to a case that does not follow the present exemplary embodiment. 
       FIGS. 19A and 19B  are graphs showing the quality of reconstructed images variously acquired from truncated measured data.  FIG. 19A  illustrates a root mean square error (RMSE) with respect to a repetition number, and  FIG. 19B  illustrates a relative RMSE (rRMSE) with respect to the repetition number. In  FIG. 19A , RMSE denotes linear attenuation (mm −1 ), and the unit of rRMSE in  FIG. 19B  is percentage (%). 
     Referring to  FIGS. 19A and 19B , line t 11  denotes RMSE and rRMSE when the measured data acquired by imaging the object at a radiation dose of 100% using an analytical reconstruction technique. Line t 12  denotes RMSE and rRMSE when the measured data acquired by imaging the object at a radiation dose of 50% using the analytical reconstruction technique. 
     Lines t 13  and t 14  indicate a case in which the measured data acquired by imaging the object at a radiation dose of 50% is acquired according to an exemplary embodiment. Line t 13  indicates a case in which a process of alternately estimating the ROI-outside measured data and the ROI-inside measured data according to an exemplary embodiment is performed once, and line t 14  indicates a case in which the above process is performed twice. 
     Lines t 13  and t 14  respectively denote RMSE and rRMSE of a reconstructed image acquired according to the repetition number of the iterative reconstruction process, when the reconstructed image is acquired from the estimated ROI-inside measured data using the iterative reconstruction technique. For line t 13 , the repetition number of the iterative reconstruction process may be optimized at the number of 11. 
     RMSE and rRMSE may be acquired through Equation 1 and Equation 2. 
     
       
         
           
             
               
                 
                   
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     In Equations 1 and 2, “x” denotes a reconstructed image and “x ref ” denotes a ground truth image. 
     Since line t 14  denotes RMSE and rRMSE that are lower than line t 13 , it may be seen that the quality of a reconstructed image is further improved as the process of alternately estimating the ROI-outside measured data and the ROI-inside measured data according to an exemplary embodiment. 
     Also, since lines t 13  and t 14  according to an exemplary embodiment have RMSE and rRMSE that are lower than line t 12  using the analytical reconstruction, the quality of an image is remarkably improved. Also, it may be seen that lines t 13  and t 14  in which a radiation dose is 50% have RMSE and rRMSE lower than line t 11  in which a radiation dose is 100%. In other words, according to an exemplary embodiment, not only artifacts due to truncation but also errors due to low radiation dose may be overcome. 
       FIG. 20  is a flowchart of a method (S 300 ) of operating a medical imaging apparatus according to an exemplary embodiment. 
     Referring to  FIG. 20 , the medical imaging apparatus may acquire measured data (S 310 ). The medical imaging apparatus may acquire an initial image based on the measured data (S 320 ). 
     The medical imaging apparatus may estimate initial ROI-inside measured data based on the measured data and the initial image (S 330 ). 
     The medical imaging apparatus may estimate ROI-outside measured data based on the initial ROI-inside measured data (S 340 ). The medical imaging apparatus may estimate the ROI-inside measured data based on a difference between the measured data and the ROI-outside measured data (S 350 ). 
     The medical imaging apparatus may determine whether to update the ROI-outside measured data and the ROI-inside measured data (S 360 ). When it is determined to update, the medical imaging apparatus may update the estimated ROI-outside measured data and the estimated ROI-inside measured data by re-performing the operations S 340  and S 350 . 
     The medical imaging apparatus may perform an update operation including the updating the ROI-outside measured data and the updating the ROI-inside measured data by iteratively performing the operations S 340 , S 350 , and S 360  until it is determined to stop updating in operation S 360 . 
     When the update is stopped, the medical imaging apparatus may acquire the reconstructed image based on the finally estimated ROI-inside measured data (S 370 ). 
     The method S 300  of operating a medical imaging apparatus of  FIG. 20  may be performed by the medical imaging apparatus  300  of  FIG. 8 . Also, all the above descriptions may be applied to the method S 300  of operating the medical imaging apparatus of  FIG. 20 . 
       FIG. 21  is a block diagram of a process in which a medical imaging apparatus acquires a reconstructed image from the measured data, according to an exemplary embodiment. 
     Referring to  FIG. 21 , the medical imaging apparatus may acquire an initial image  91  by reconstructing measured data  90  (S 31 ). 
     The medical imaging apparatus may acquire initial ROI-outside RP data  91   r  by re-projecting (RP) the outside of ROI in the initial image  91 . The medical imaging apparatus may estimate a difference between the initial ROI-outside RP data  91   r  and the measured data  90  as initial ROI-inside measured data  92  (S 32 ). 
     The medical imaging apparatus may acquire an initial ROI-inside image  93  by reconstructing the initial ROI-inside measured data  92  (S 33 ). 
     The medical imaging apparatus may acquire ROI-inside RP data  93   r  by re-projecting the initial ROI-inside image  93 . The medical imaging apparatus may estimate a difference between the ROI-inside RP data  93   r  and the measured data  90  as ROI-outside measured data  94  (S 34 ). 
     The medical imaging apparatus may acquire an ROI-outside image  95  by reconstructing the ROI-outside measured data  94  (S 35 ). 
     The medical imaging apparatus may acquire ROI-outside RP data  95   r  by re-projecting the ROI-outside image  95 . The medical imaging apparatus may estimate a difference between the ROI-outside RP data  95   r  and the measured data  90  as ROI-inside measured data  96  (S 36 ). 
     The medical imaging apparatus may acquire an ROI-inside image  97  by reconstructing the ROI-inside measured data  96  (S 37 ). 
     The medical imaging apparatus may determine whether to update the ROI-outside measured data and the ROI-inside measured data (S 38 ). 
     When the update is determined, the medical imaging apparatus may update the ROI-outside measured data  94  based on the ROI-inside image  97 , not the initial ROI-inside image  93 , the ROI-inside measured data  96  based on the updated ROI-outside measured data  94 , and the ROI-inside image  97  based on the updated ROI-inside measured data  96 . As such, the medical imaging apparatus may iteratively perform the operations S 34 , S 35 , S 36 , S 37 , and S 38  until the stop of the update is determined in the operation S 38 . 
     When it is determined to stop the updating in operation S 38 , the medical imaging apparatus may acquire a reconstructed image  98  based on the finally updated ROI-inside image  97 . 
       FIG. 22  is a block diagram of a structure of a medical imaging apparatus  400  according to an exemplary embodiment. 
     Referring to  FIG. 22 , the medical imaging apparatus  400  may include a communication unit  410  and an image processor  420 . The communication unit  410  may be a structure corresponding to the data acquirer  310  of the medical imaging apparatus  300  of  FIG. 8  or may be included in the data acquirer  310 . The communication unit  410  may receive measured data from an external device. The external device may be a medical apparatus including an X-ray source, and the medical apparatus may acquire the measured data by imaging an object and transmit the measured data to the medical imaging apparatus  400 . 
     The image processor  420  may acquire a reconstructed image from the measured data received from the communication unit  410 . Since all the above descriptions may be applied to the method of acquiring a reconstructed image from the measured data, a redundant description is omitted. 
       FIG. 23  is a block diagram of a structure of a medical imaging apparatus  500  according to an exemplary embodiment. 
     Referring to  FIG. 23 , the medical imaging apparatus  500  may include a communication unit  510 , an image processor  520 , and an output unit  530 . The elements included in the medical imaging apparatus  500  may be connected to each other by a connection method  590  that may be wired or wireless. 
     Since the communication unit  510  and the image processor  520  of  FIG. 23  respectively correspond to the communication unit  410  and the image processor  420  of  FIG. 22 , a redundant description is omitted. 
     The output unit  530  may output the reconstructed image acquired by the image processor  126  on the screen of the output unit  530 . The output unit  530  may further output the data and image acquired in the process of acquiring the reconstructed image from the measured data according to an exemplary embodiment. 
     The output unit  530  may output information that is necessary for the user to manipulate the medical imaging apparatus  500 , for example, a user interface (UI), user information, or object information. Examples of the output unit  530  may include a speaker, a printer, a cathode ray tube (CRT) display, a liquid crystal display (LCD), a plasma display panel (PDP), an organic light emitting diode (OLED) display, a field emission display (FED), a light emitting diode (LED) display, a vacuum fluorescent display (VFD), a digital light processing (DLP) display, a flat panel display (FPD), a three-dimensional (3D) display, a transparent display, and other various output devices well known to one of ordinary skill in the art. 
       FIG. 24  is a block diagram of a structure of a medical imaging apparatus  600  according to an exemplary embodiment. 
     Referring to  FIG. 24 , the medical imaging apparatus  600  may include a communication unit  610 , an image processor  620 , an output unit  630 , an input unit  640 , and a storage unit  650 . The elements included in the medical imaging apparatus  600  may be connected to each other by a connection method  690  that may be wired or wireless. 
     Since the communication unit  610 , the image processor  620 , and the output unit  630  of  FIG. 24  respectively correspond to the communication unit  510 , the image processor  520 , and the output unit  530  of  FIG. 23 , a redundant description is omitted. 
     The input unit  640  may receive from a user a command to control the medical imaging apparatus  600 . The input unit  640  may receive from a user information for determining the repetition number of update operations including updating the ROI-outside measured data and updating the ROI-inside measured data. Also, the user may set parameters related to estimation or updating the ROI-outside measured data through the input unit  640 . For example, the parameter may include the size of an object or ROI-outside reconstruction parameters. 
     The output unit  630  and the input unit  640  may provide the user with a user interface (UI) for manipulating the medical imaging apparatus  600 . The output unit  630  may output a UI. 
     The storage unit  650  may store various pieces of information or data for the operation of the medical imaging apparatus  600 . Also, the storage unit  650  may store the data or image acquired during the process of acquiring a reconstructed image from the measured data according to an exemplary embodiment. 
       FIG. 25  is a flowchart of a method (S 400 ) of operating a medical imaging apparatus according to an exemplary embodiment. 
     Referring to  FIG. 25 , the medical imaging apparatus may acquire measured data (S 410 ). The medical imaging apparatus may acquire an initial image based on the measured data (S 420 ). 
     The medical imaging apparatus may alternately estimate ROI-outside measured data and ROI-inside measured data based on the measured data and the initial image (S 430 ). The medical imaging apparatus may output an ROI-inside image acquired based on the ROI-inside measured data (S 440 ). 
     The medical imaging apparatus may receive an input of whether to approve the output ROI-inside image from the user (S 450 ). When the approval is not input, the medical imaging apparatus may update the ROI-outside measured data and the ROI-inside measured data by re-performing the operations S 430  and S 440 , and may output an updated ROI-inside image. The medical imaging apparatus may receive again an input of whether to approve the updated ROI-inside image from the user (S 450 ). In other words, the medical imaging apparatus may iteratively re-perform the operations S 430  to S 450  until the user&#39;s approval is input. 
     Alternatively, if a user&#39;s input for re-performing the operations S 430  and S 440  or updating ROI-inside image is not inputted or a user inputs nothing, it may be assumed that the user approves the currently output ROI-inside image. 
     When the user&#39;s approval is input, the medical imaging apparatus stops the update operation. The medical imaging apparatus may acquire a reconstructed image based on the finally output ROI-inside image (S 460 ). 
     The method (S 400 ) of operating the medical imaging apparatus of  FIG. 25  may be performed by the medical imaging apparatus  600  of  FIG. 24 . However, the present disclosure is not limited thereto. Also, all the above descriptions may be applied to the method (S 400 ) of operating the medical imaging apparatus of  FIG. 25 . 
     The medical imaging apparatus according to an exemplary embodiment may be an X-ray apparatus or may be included in an X-ray apparatus. 
       FIG. 26  is a block diagram of a structure of an X-ray apparatus  700  according to an exemplary embodiment. 
     Referring to  FIG. 26 , the X-ray apparatus  700  may include an X-ray source  710 , a detector  720 , and an image processor  730 . The elements included in the X-ray apparatus  700  may be connected to each other by a connection method  790  that may be wired or wireless. 
     The X-ray apparatus  700  may acquire measured data through the X-ray source  710  and the detector  720 . The image processor  730  may acquire a reconstructed image from the measured data. Since the operation of each structure is already described above, a redundant description is omitted. 
     In the above description, the medical imaging apparatus is described as an apparatus that is included in an X-ray apparatus or may receive the measured data by being connected to the X-ray apparatus by a wired or wireless method. However, the medical apparatus related to the medical imaging apparatus according to an exemplary embodiment is not limited to the X-ray apparatus. The method of operating a medical image according to an exemplary embodiment may be used for various medical apparatus including, for example, not only the X-ray apparatus, but also a CT apparatus, a CT apparatus for dental use, cone beam Computed Tomography (CBCT), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), Optic Coherence Tomography (OCT), etc. 
       FIG. 27  is a schematic view of a CT apparatus  200  to which an exemplary embodiment is applicable. 
     Referring to  FIG. 27 , the CT apparatus  200  may include a gantry  202 , a table  205 , an X-ray source  206 , and a detector  208 . The gantry  202  may include the X-ray source  206  and the detector  208 . The object  10  may be located on the table  205 . 
     The table  205  may be moved in a predetermined direction, for example, at least one of upward, downward, left, and right directions, in a CT imaging process. Also, the table  205  may be rotated or tilted in a predetermined direction by a predetermined angle. The gantry  202  may also be tilted in a predetermined direction by a predetermined angle. 
       FIG. 28  is a block diagram of a structure of a CT apparatus  800  according to an exemplary embodiment. 
     Referring to  FIG. 28 , the CT apparatus  800  may include a gantry  815  including an X-ray source  810  and a detector  820 , and an image processor  830 . The elements included in the CT apparatus  800  may be connected to each other by a connection method  890  that may be wired or wireless. 
     The CT apparatus  800  may acquire measured data through the X-ray source  810  and the detector  820  that rotate together. The image processor  830  may acquire a reconstructed image from the measured data. Since all the descriptions may be applied to the operation of each element, a redundant description is omitted. 
     The exemplary embodiments of the present disclosure can be written as computer programs and can be implemented in general-use digital computers that execute the programs using a non-transitory computer readable recording medium. 
     Examples of the non-transitory computer readable recording medium include magnetic storage media (e.g., floppy disks, hard disks, etc.), optical recording media (e.g., CD-ROMs, DVDs, etc.), integrated circuit storage media (e.g., FLASH memory, read only memory (ROM), erasable programmable ROM (EPROM), etc.), as well as others suitable for storing computer programs. 
     It should be understood that exemplary embodiments described herein should be considered in a descriptive sense only and not for purposes of limitation. Descriptions of features or aspects within each exemplary embodiment should typically be considered as available for other similar features or aspects in other exemplary embodiments. 
     While one or more exemplary embodiments have been described with reference to the figures, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the disclosure as defined by the following claims.