Patent Description:
Dilations of vessels in the human body are a severe risk for a patient, since these dilations, in particular in the aorta, may progress towards an aneurysm which may burst or cause other adverse effects such as heart attacks, kidney damage or stroke. Thus, early detection of such dilations is critical for many diseases, e.g. for the aorta, i.e. aortic dissection, aortic rupture, and ruptured abdominal aortic aneurysms. Left untreated, such diseases often have severe and potentially fatal consequences. Therefore, it is important to monitor the progression of a dilation of a particular organ.

Additionally, in a post-operative scenario, e.g. after an endovascular aneurysm repair, sac shrinkage is considered to be evidence of clinical success. The problem also can be generalized to any hollow organ such as e.g. other vessels like the airways, or the trachea.

Conventionally, changes of hollow organs are diagnosed by manual evaluation of medical images of a patient, e.g. ultrasound, MR or CT images of an organ under investigation. However, such dilations or shrinkages are often asymptomatic and are only detected after complications have manifested. Thus, it is not possible to diagnose such changes before complications have manifested, resulting in a delayed diagnosis or a failure to diagnose.

Document <CIT> discloses a method for visualizing the anatomy of a region of interest of a tubular-shaped organ based on acquired three-dimensional image slices of the region of interest. Comparison between different points in time are based on a registration of the tubular-shaped organs itself.

Document <CIT> discloses to identify changes in a tubular tissue structure within a living being by comparing two volume data records generated at different times. Changes in the minimum and/or maximum diameter of the inner and/or outer wall of the tubular tissue structure are established by comparing corresponding positions along the midlines of the tubular tissue structure in the two volume data records. Document <CIT> discloses methods for determining the centerline of a hollow organ section using image data. It involves setting a start location, defining search rays, identifying penetration points, conducting principal component analysis, fitting a geometric figure, deriving a new start location, and recursively performing these steps until a centerline is formed.

It is the object of the present invention to improve the known systems, devices and methods to facilitate an improvement in automatic determining the change of hollow organs.

This object is achieved by a method according to claim <NUM> and a device according to claim <NUM>.

A method according to the invention for automatic determination of the change of a hollow organ, typically on the basis of medical images, and especially also for the visualization of the results, is defined by the features of claim <NUM> including the following steps:.

In those steps the reference-lines (L1, L2) are centerlines (L1, L2) of the hollow organ (O).

In addition, the results can be displayed for a user, as described in more detail below.

Concerning the expression "features" (can also be denominated as "properties" or "measurements" or "datasets"), the features represent a set of parameter values determined in the images. These parameters can be e.g. distances, cross sections or other "features" of the organ that can be measured. It is preferred that a feature comprises a whole set of parameter values measured along a predefined part of the reference-line (e.g. the whole reference-line).

Regarding the steps providing the medical images of the hollow organ, they should be recorded at two different points of time, one earlier (e.g. the first point of time) and one later (e.g. the second point of time). The organ may have changed between the two points of time and that change will be visible with this method. Although it is preferred that the images are 3D images, they also could be 2D images or stacks of 2D images. It is not important, what recording technique is used. However, the images should be digital images (or digitalized images) and are preferably CT-images (CT: computer tomography), MR-images (MR: magnet resonance), X-ray images or ultrasound images, e.g. from thoracic and/or abdominal (CT/MRI) acquisitions. Surely, the images should be from the same organ of the same patient. However, it is also possible, that the images are from two different patients in order to compare the two (similar) organs. These images are in the further process used to determine (and visualize) the change (progression or shrinkage) of the hollow organ under investigation.

Regarding the representations of the organ in the images it should be noted that initially there are only pixels (here, "pixel" also stands for "voxel") in the images. The organ must be made "known" for the method for that only the organ in the images is treated. Thus, the method determines the representation of the organ, that is the pixels representing the organ in the images, or another computerized representation as e.g. a surface mesh created from the pixels, an implicit formulation or a segmentation mask. For the following steps, this representation of the organ under investigation from the two images is used. For example, for the aorta these masks might have been obtained automatically using an automatic detection and quantification of the organ from the medical images, i.e. by performing automatic segmentation of the organ. However, the representation could also be generated manually or semi-automatically.

Regarding the steps of computing the reference-lines of the organ, the representations of the organ are used, since they represent the organ and not the information of the whole images. A reference line is a (typically theoretical) line characterizing the shape of the organ (e.g. straight or curved). Preferably, the reference line follows the outer/inner shape and/or the course of the hollow organ in the body of a patient. For two identical organs the reference lines are also identical.

A reference line is the centerline, i.e. a line leading through the center points of the cross sections of the hollow organ. The calculation of a centerline is based on an iterative calculation of a point d of the centerline based on a known point dprev (previously calculated) on the centerline, wherein point d has a definite distance δ to point dprev (or in a mathematical notation: ||d-dprev||=δ). For calculating the centerline, the optimization problem <MAT> has to be solved, wherein S is the set of all points on the surface of the hollow organ and p is a point in S. To achieve a smooth centerline, it is preferred to include a regularization that confines the changes in the direction of the centerline. As an initial starting point, an anatomically unique defined point should be chosen, e.g. a point in the center of a cross section of the organ, preferably at one end on the picture of the organ. The center line follows the length of the organ, e.g. the vector of a laminar blood flow in a blood vessel.

However, other lines are also preferred as reference lines, e.g. a line following the surface or the wall of the organ (or a number of lines representing the inner or outer shape of the organ, where in the lines of a mesh could also be used as reference lines). The line does not necessarily need to follow the shape of the organ directly but may follow the shape e.g. in a spiral way. The reference line does not have necessarily to be one single line but can e.g. comprise two or more lines or may split or branch (e.g. when characterizing the bronchia or blood vessels, such as the pulmonary artery or the carotid artery).

Regarding the registration of the first and the second reference line, the goal is to determine a mapping of each point on one of the reference lines to a unique point on the other reference line. Using this mapping, the organ representations and/or features derived from the representations can be compared to each other. Typically, one reference line serves as target and the other reference line is transformed to match this target (wherein however, it is also possible to transform both sides). The techniques of graphical registration (also known as co-registration) are well known. Since the reference lines may also characterize the inner or outer shape of the representation of the organ, or a mesh of this representation, the registering process can theoretically also be based on the shape of the complete representation of the organ, e.g. a surface mesh or a segmentation mask. The registration is preferably a rigid registration, wherein non-rigid registrations are also possible.

Regarding the comparison of the matched representations of the organ and/or between features derived from these representations, there are numerous possibilities. Distances, cross sections or volumes could be calculated in the representations of the organ and compared with another. Surely, they must be depending on characterizing coordinates that are similar in the two representations. Thanks to the registration, for each feature at a particular location of the organ in the first data set a matching feature at the corresponding location in the second data set exists and can be compared. Change can be quantified and visually highlighted. It should be noted that by comparing features derived from the representations, quantitative results can be achieved, absolute or differences or ratios. It should also be noted that differences between pixels in the images could also be a useful comparison, wherein the positions of these pixels would be the corresponding feature. Typically, the images are recorded with a similar medical imaging system and the features measured there are automatically comparable. However, if there is the need (e.g. if the organ is pictured bigger on one image), the images or at least the representations can also be registered, especially by using the same transformations used for registering the reference lines.

A device according to the invention for automatic determination of the change of a hollow organ comprises the features of claim <NUM>, including the following components:.

It should be noted that the device may comprise one single component of the respective units to compute both, first and second means, or an individual unit for the first means and an individual unit for the second means. For example, the reference unit may comprise two components, one to compute the first reference-line and one to compute the second reference-line, and one single segmentation unit for computing both, the first representation of the organ in the first image and the second representation of the organ in the second image.

In the device the reference-lines are centerlines of the hollow organ.

A control device according to the invention for controlling a medical imaging system, e.g. a CT-system or an MRI-system, comprises a device according to the invention. Alternatively or additionally it is designed to perform the method according to the invention. The control device may comprise additional units or devices for controlling components of a medical imaging device, e.g. a CT-system or a MRI-system, such as a X-ray unit, a sequence control unit for measurement sequence control, a memory, a radio-frequency transmission device that generates, amplifies and transmits RF pulses, a gradient system interface, a radio-frequency reception device to acquire magnetic resonance signals and/or a reconstruction unit to reconstruct magnetic resonance image data.

A medical imaging system, e.g. a magnetic resonance imaging system or a computer tomography system, comprises a control device according to the invention.

Some units or modules of the device or the control device mentioned above can be completely or partially realized as software modules running on a processor of a device or a control device. A realization largely in the form of software modules can have the advantage that applications already installed on an existing system can be updated, with relatively little effort, to install and run these units of the present application. The object of the invention is also achieved by a computer program product with a computer program that is directly loadable into the memory of a device of a device or a control device of a medical imaging system, and which comprises program units to perform the steps of the inventive method when the program is executed by the control device or the device. In addition to the computer program, such a computer program product can also comprise further parts such as documentation and/or additional components, also hardware components such as a hardware key (dongle etc.) to facilitate access to the software.

A computer readable medium such as a memory stick, a hard-disk or other transportable or permanently-installed carrier can serve to transport and/or to store the executable parts of the computer program product so that these can be read from a processor unit of a control device or a device. A processor unit can comprise one or more microprocessors or their equivalents.

A preferred method comprises the following steps:.

These distances and/or cross sections are features derived from the representations mentioned above. The surface of the organ thereby denotes the set of points belonging to the surface of the representation of the organ, e.g. the vertices of the surface mesh or the pixels at the boundary of the segmentation mask. The distances and cross sections are measured from predefined coordinates of the reference lines to points on the surface of the organ. Due to the prior registration of the reference lines the coordinates and hence the points on the first and the second representation pairwise correspond. Thus, the measured distances and cross sections are pairwise comparable.

Regarding the device, it is preferred that it additionally comprises:.

wherein the registration unit is designed for registering the two reference lines to obtain a matching representation of the organ, and the comparison-unit is designed for comparing the measured distances and/or cross sections pairwise with the respective matched distances and/or cross sections, especially including a quantification of change. Thus, the comparing unit is designed for determining changes between the distances by comparing the first set of distances and/or cross sections with the second set of distances and/or cross sections of corresponding coordinates of the reference lines, preferably by computing ratios and/or differences of corresponding distances and/or cross sections. The measuring unit is preferably be part of the comparison-unit.

According to the invention, the reference-lines are centerlines of the hollow organ. These centerlines are determined by an iterative calculation. In the course of this calculation, the next point d of a centerline is computed based on a known or predefined point dprev on the centerline with a predefined distance (δ, see above) between points d and dprev and the surface S of the hollow organ by solving the optimization problem mind maxp∈S ∥d-p∥ (see above formula (<NUM>)).

According to a preferred method, measurements are performed for the organ in order to obtain (relative and/or absolute) values of the size of parts of the organ. Preferably, the measurements are performed for a predefined set of points of the reference line, especially each (digital) point on the reference-line. The measurements preferably include the maximum diameter of the organ and/or the average diameter of the organ and/or the cross-sectional area of the organ at a predefined coordinate on the reference-line. For example, as a result, 1D profiles of the measurements along each centerline can be generated characterizing e.g. the course of the maximum diameter along the aorta. After that, the measurements from the two datasets can be compared point-by-point for predefined points on the centerline.

According to a preferred method, the reference lines are registered by using numerical optimization techniques. It is preferred that the registration is performed by applying a rigid or non-rigid spatial transformation, especially a transformation of the shift, rotation, stretch and/or warp, to the points on one of the centerlines. Typically, the registration is performed in order to get the best match between the two centerlines, i.e. to obtain a set of pairwise matching points on the two centerlines.

According to a preferred method, the matching points on the two reference lines are used for determining changes between the features derived from the representations of the organ. It should be noted that each matching point corresponds to a matching point on the first reference line (to form a pair as mentioned above).

According to a preferred method, the determined changes between the representations of the organ and/or between features determined from these representations are visualized. This is preferably done in form of a 3D-image showing the representation of the organ and the determined changes. Alternatively or additionally, this is preferably done in form if a 2D-diagram, wherein the points along the reference line are interpreted as points on one axis of the 2D diagram and the changes relative to each point is shown on the other axis. Especially, the points along the reference line (e.g. a centerline) are interpreted as points along a (curved) first axis for a 2D-visualization. Then, die distances are mapped on a second axis corresponding to coordinates on the first axis. If the centerline has been sampled equidistantly, also those points on the axis should be equidistant. The measurements or their change are mapped to the other axis.

According to a preferred method, the determined changes between the representations of the organ and/or between features derived from these representations are labeled or marked depending on the quantity of change (including absolute quantities and/or relative quantities, e.g. ratios). In the case the quantity of change is bigger than a predefined threshold it is preferred that a warning is provided, especially in the form of a special label, a special marker, a warning message and/or an acoustic signal. According to a preferred visualization method, the surface of the organ of at least one of the two representations is rendered in 3D. In this case, the change of a particular measurement could be displayed as different colors across the surface of the organ. For each point on the surface the color is thereby chosen according to the value of the changes of the corresponding point relative to the reference line. Colors should be chosen to highlight significant change, e.g. mark a severe diameter increase in red and stable regions in green or a neutral color. Vice versa, in a post-operative scenario a successful shrinkage might be marked in green or blue.

According to a preferred method, a graphical filter function, preferably smoothing and/or a gaussian filter is applied to the features derived from the organ representations and/or to the image visualizing changes. The filter is e.g. applied before plotting to suppress noise in the visualization.

In a preferred device according to the invention, components of the device are part of a data-network, wherein preferably the data-network and a medical imaging system (i.e. a magnetic resonance imaging system or a computer tomography imaging system which provide image data) are in data-communication with each other, wherein the data-network preferably comprises parts of the internet and/or a cloud-based computing system, wherein preferably the device according to the invention or a number of components of this system is realized in this cloud-based computing system. For example, the components of the system are part of a data-network, wherein preferably the data-network and a medical imaging system which provides the image data are in communication with each other. Such a networked solution could be implemented via an internet platform and/or in a cloud-based computing system.

The method may also include elements of "cloud computing". In the technical field of "cloud computing", an IT infrastructure is provided over a data-network, e.g. a storage space or processing power and/or application software. The communication between the user and the "cloud" is achieved by means of data interfaces and/or data transmission protocols.

In the context of "cloud computing", in a preferred embodiment of the method according to the invention, provision of data via a data channel (for example a data-network) to a "cloud" takes place. This "cloud" includes a (remote) computing system, e.g. a computer cluster that typically does not include the user's local machine. This cloud can be made available in particular by the medical facility, which also provides the medical imaging systems. In particular, the image acquisition data is sent to a (remote) computer system (the "cloud") via a RIS (Radiology Information System) or a PACS (Picture Archiving and Communication System).

Within the scope of a preferred embodiment of the system according to the invention, the abovementioned units (data interface, the mentioned units) are present on the "cloud" side. A preferred system further comprises, a local computing unit connected to the system via a data channel (e.g. a data-network, particularly configured as RIS or PACS). The local computing unit includes at least one data receiving interface to receive data. Moreover, it is preferred if the local computer additionally has a transmission interface in order to send data to the system.

The proposed measurement and visualization system allows for a fully automatic quantitative comparison of the size parameters (diameter, cross-sectional area) of hollow organs, in particular vessels depicted in two imaging data sets (in particular if combined with an automatic detection and segmentation technique). Moreover, the advanced visualization allows for a very intuitive and fast interpretation of the measured change.

In the diagrams, like numbers refer to like objects.

<FIG> shows a block diagram of the process flow of a preferred method according to the invention for automatic determination of the change of a hollow organ O (see. e.g. <FIG>).

In step I, a first medical image P1 of the organ O is provided that had been recorded at a first point of time, e.g. with an imaging device <NUM> as shown in <FIG>.

In step II, a second medical image P2 of the organ O is provided that had been recorded at a (later) second point of time, e.g. also with an imaging device <NUM> as shown in <FIG>.

In step III, a first representation R1 of the organ O in the first image P1 and a second representation R2 of the organ O in the second image P2 is computed. This could be performed in one single step or in two different (sub-)steps.

In step IV, a first reference-line L1 of the organ O is calculated based on the first representation R1 of the organ O, and a second reference-line L2 of the organ O is calculated based on the second representation R2 of the organ O. This could be performed in one single step or in two different (sub-)steps.

In step V, the reference-line L1 and L2 are registered obtaining matching representations of R1 and R2 of the organ O.

In step VI, a first set of features D1 (here e.g. distances D1 from a point of the reference line L1 to a point on the surface S of the organ O pictured in the first medical image P1) is determined at a set of predefined coordinates C1 of the first reference-line L1 and a second set of features D2 (here e.g. distances D2 from a point of the reference line L2 to a point on the surface S of the organ O pictured in the second medical image P2) is determined at the set of predefined coordinates C2 of the second reference-line L2. For this step, see also <FIG>.

In step VII, changes between the features D1, D2 are determined by comparing the first set of features D1 with the second set of features D2 of corresponding coordinates C1, C2 of the reference lines L1, L2, preferably by computing ratios and/or differences.

In step VIII, the determined changes are visualized.

<FIG> shows a schematic representation of a magnetic resonance imaging system <NUM> ("MRI-system"). This example should show that not only CT-images could be used, but images recorded with any other medical imaging system. There could even be compared two images recorded with different medical imaging systems.

The MRI system <NUM> includes the actual magnetic resonance scanner (data acquisition unit) <NUM> with an examination space <NUM> or patient tunnel in which a patient or test person is positioned on a driven bed <NUM>, in whose body the actual examination object, the organ O is located.

The magnetic resonance scanner <NUM> is typically equipped with a basic field magnet system <NUM>, a gradient system <NUM> as well as an RF transmission antenna system <NUM> and an RF reception antenna system <NUM>. In the shown exemplary embodiment, the RF transmission antenna system <NUM> is a whole-body coil permanently installed in the magnetic resonance scanner <NUM>, in contrast to which the RF reception antenna system <NUM> is formed as local coils (symbolized here by only a single local coil) to be arranged on the patient or test subject. In principle, however, the whole-body coil can also be used as an RF reception antenna system, and the local coils can respectively be switched into different operating modes.

The basic field magnet system <NUM> is designed that 3D images P1, P2 can be recorded. It here is designed in a typical manner so that it generates a basic magnetic field in the longitudinal direction of the patient, i.e. along the longitudinal axis of the magnetic resonance scanner <NUM> that proceeds in the z-direction. The gradient system <NUM> typically includes individually controllable gradient coils in order to be able to switch (activate) gradients in the x-direction, y-direction or z-direction independently of one another.

The MRI system <NUM> shown here is a whole-body system with a patient tunnel into which a patient can be completely introduced. However, in principle the invention can also be used at other MRI systems, for example with a laterally open, C-shaped housing, as well as in smaller magnetic resonance scanners in which only one body part can be positioned.

Furthermore, the MRI system <NUM> has a central control device <NUM> that is used to control the MRI system <NUM>. This central control device <NUM> includes a sequence control unit <NUM> for measurement sequence control. With this sequence control unit <NUM>, the series of radio-frequency pulses (RF pulses) and gradient pulses can be controlled depending on a selected pulse sequence within a measurement or control protocol. Different control protocols for different measurements or measurement sessions are typically stored in a memory <NUM> and can be selected by and operator (and possibly modified as necessary) and then be used to implement the measurement.

To output the individual RF pulses of a pulse sequence, the central control device <NUM> has a radio-frequency transmission device <NUM> that generates and amplifies the RF pulses and feeds them into the RF transmission antenna system <NUM> via a suitable interface (not shown in detail). To control the gradient coils of the gradient system <NUM>, the control device <NUM> has a gradient system interface <NUM>. The sequence control unit <NUM> communicates in a suitable manner with the radio-frequency transmission device <NUM> and the gradient system interface <NUM> to emit the pulse sequence.

Moreover, the control device <NUM> has a radio-frequency reception device <NUM> (likewise communicating with the sequence control unit <NUM> in a suitable manner) in order to acquire magnetic resonance signals (i.e. raw data) for the individual measurements, which magnetic resonance signals are received in a coordinated manner from the RF reception antenna system <NUM> within the scope of the pulse sequence.

A reconstruction unit <NUM> receives the acquired raw data and reconstructs magnetic resonance image data therefrom for the measurements. This reconstruction is typically performed on the basis of parameters that may be specified in the respective measurement or control protocol. For example, the image data can then be stored in a memory <NUM>.

Operation of the central control device <NUM> can take place via a terminal <NUM> with an input unit and a display unit <NUM>, via which the entire MRI system <NUM> can thus also be operated by an operator. MR images can also be displayed at the display unit <NUM>, and measurements can be planned and started by means of the input unit (possibly in combination with the display unit <NUM>), and in particular suitable control protocols can be selected (and possibly modified) with suitable series of pulse sequence as explained above.

The control device <NUM> comprises a device <NUM> designed to perform the method according to the invention. This device <NUM> comprises the following components that may appear to be software modules.

A data interface <NUM> designed for receiving a first medical image P1 of the organ O recorded at a first point of time, and a second medical image P2 of the organ O recorded at a second point of time.

A segmentation unit <NUM> designed for computing a first representation R1 of the organ O in the first image P1 and a second representation R2 of the organ O in the second image P2.

A reference unit <NUM> designed for computing a first reference-line L1 of the organ O based on the first representation R1 of the organ O and a second reference-line L2 of the organ O based on the second representation R2 of the organ O.

A registration-unit <NUM> designed for registering of the first reference-line L1 and the second reference-line L2 to obtain a matching of the two representations R1, R2 of the organ O and/or features D1, D2 derived from the representations R1, R2.

A measuring unit <NUM> designed for determining a first set of distances D1 from a set of predefined coordinates C1 of the first reference-line L1 to a surface of the organ O pictured in the first medical image P1 (see e.g. the following figures) and a second set of distances D2 from the set of predefined coordinates C2 of the second reference-line L2 to the surface of the organ O pictured in the second medical image P2.

A comparison-unit <NUM> designed for comparing the matched representations R1, R2 of the organ O and/or the features D1, D2 derived from these representations R1, R2. The measuring unit <NUM> could also be a part of the comparison unit <NUM>.

The results could be sent to the data interface <NUM> again, if it is a bilinear interface (dashed arrow) and shown on the display unit <NUM>.

The MRI system <NUM> according to the invention, and in particular the control device <NUM>, can have a number of additional components that are not shown in detail but are typically present at such systems, for example a network interface in order to connect the entire system with a network and be able to exchange raw data and/or image data or, respectively, parameter maps, but also additional data (for example patient-relevant data or control protocols).

The manner by which suitable raw data are acquired by radiation of RF pulses and the generation of gradient fields, and MR images are reconstructed from the raw data, is known to those skilled in the art and thus need not be explained in detail herein.

<FIG> shows two representations R1, R2 of an organ O in form of segmentation masks of two images P1, P2 of the aorta obtained from two CT data sets (images P1, P2, see e.g. <FIG>) at two time points T1 and T2. The images P1, P2 could also be acquired by an MRI-system as shown in <FIG>. These segmentation masks are obtained from two images P1, P2 that have been recorded a few months after another. It can be seen that the aortic root is larger in the right representation R2 as compared to the left representation R1 (dashed lines in the right representation R2 represent the shape of the left representation R1). In the representations R1, R2 centerlines L1, L2 are shown and a distance D1, D2 for each representation R1, R2. The distance should represent a feature, wherein typically, a feature is preferably a plurality of distances, especially distances measured to points on the wall of the organ throughout the whole reference line.

<FIG> shows the aligned (co-registered) centerlines L1, L2 in a 3D space obtained from the two representations displayed in <FIG>. The unit of the measures is mm.

<FIG> shows the plots of three features (measurements) (upper graphs) as well as their difference (lower graphs). The coordinates C1, C2 of the centerlines L1, l2 are mapped to the x-axis of the graphs and the differences of the features for the coordinates C1, C2 are shown on the y-axis. From left to right, the maximum diameter (left), the average diameter (middle) and the cross-sectional area (right) are plotted.

<FIG> shows the change in maximum diameter in 3D. Here the representation R1 of the first image P1 is shown with hatching structures. The greater the difference between distances D1, D2 is, the denser is the hatching.

Claim 1:
A computer-implemented method for automatic determination of the change of a hollow organ (O) comprising the steps:
- providing a first medical image (P1) of the organ (O) recorded at a first point of time (T1),
- computing a first representation (R1) of the organ (O) in the first image (P1),
- computing a first reference-line (L1) of the organ (O) based on the first representation (R1) of the organ (O),
- providing a second medical image (P2) of the organ (O) recorded at a second point of time (T2),
- computing a second representation (R2) of the organ (O) in the second image (P2),
- computing a second reference-line (L2) of the organ (O) based on the second representation (R2) of the organ (O),
- registering of the first reference-line (L1) and the second reference-line (L2) to obtain a matching of the two representations (R1, R2) of the organ (O) and/or features (D1, D2) derived from the representations (R1, R2),
- comparing the matched representations (R1, R2) of the organ (O) and/or the features (D1, D2) derived from these representations (R1, R2),
wherein the reference-lines (L1, L2) are centerlines (L1, L2) of the hollow organ (O), wherein the reference-lines (L1, L2) are determined by an iterative calculation of the next point d of a centerline (L1, L2) based on a known or predefined point dprev on the centerline (L1, L2) with a predefined distance between points d and dprev and points p on the surface S of the hollow organ (O) by solving the optimization problem mind maxp∈S ||d-p||,
wherein the hollow organ (O) is an aorta, a vessel, an airway or a trachea.