Source: http://www.google.com/patents/US5657362?dq=7,117,286
Timestamp: 2015-01-28 21:20:21
Document Index: 213123481

Matched Legal Cases: ['application No. 07', 'application No. 08', 'application No. 08', 'application No. 08', 'application No. 08', 'application No. 08', 'application No. 08', 'application No. 08', 'application No. 08']

Patent US5657362 - For enhancing visualization of a mammographic image - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsA method and system for the automated detection of lesions such as masses and/or tissue (parenchymal) distortions in medical images such as mammograms. Dense regions and subcutaneous fat regions within a mammogram are segmented. A background correction may be performed within the dense regions. Hough...http://www.google.com/patents/US5657362?utm_source=gb-gplus-sharePatent US5657362 - For enhancing visualization of a mammographic imageAdvanced Patent SearchPublication numberUS5657362 APublication typeGrantApplication numberUS 08/393,779Publication dateAug 12, 1997Filing dateFeb 24, 1995Priority dateFeb 24, 1995Fee statusPaidAlso published asCA2188394A1, CA2188394C, DE69638305D1, EP0757544A1, EP0757544A4, EP0757544B1, WO1996025879A1Publication number08393779, 393779, US 5657362 A, US 5657362A, US-A-5657362, US5657362 A, US5657362AInventorsMaryellen L. Giger, Ming Zhang, Ping LuOriginal AssigneeArch Development CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (4), Non-Patent Citations (9), Referenced by (89), Classifications (16), Legal Events (7) External Links: USPTO, USPTO Assignment, EspacenetFor enhancing visualization of a mammographic imageUS 5657362 AAbstract A method and system for the automated detection of lesions such as masses and/or tissue (parenchymal) distortions in medical images such as mammograms. Dense regions and subcutaneous fat regions within a mammogram are segmented. A background correction may be performed within the dense regions. Hough spectrum within ROIs placed in the breast region of a mammogram are calculated and thresholded using the intensity value η in order to increase sensitivity and reduce the number of false-positive detections. Lesions are detected based on the thresholded Hough spectra. The thresholded Hough spectra are also used to differentiate between benign and malignant masses.
Mammograms are obtained using conventional radiographic techniques. The mammograms are digitized, for example, by using a laser scanner. The digital image is typically of 2048 pixels by 2500 pixels, where the pixel size is 0.1 mm. Mammograms are subsampled or averaged to obtain an effective pixel size of 0.5 mm resulting in a 512�512 image.
&#958;k =f(x,y)                                         (5)
&#950;i =h(u,v)                                       (6)
In the image of FIG. 16B, the x-coordinate of pixel B2 has to be rounded to its nearest integer, resulting in three close but different intersection points in its Hough spectrum by every two of the curves corresponding to these three pixels of line segment B1 B2 B3 . Therefore, if the pixel size of the Hough spectrum in FIG. 16D is large enough to cover the area of all three crosspoints, a correct accumulation of pixels B1, B2, and B3 can still be achieved. This manifests the importance of the appropriate quantization of the Hough spectrum. The images have an appropriate size, such as 512�512, and image pixel size, such as 0.5 mm.
FIGS. 18A-18D illustrate a simulated normal parenchymal background (18A), as well as a simulated circumscribed lesion (18B), a simulated spiculated lesion (18C), and a simulated parenchymal distortion with the presence of normal parenchymal tissue (18D). The corresponding Hough spectra are also illustrated in FIGS. 18E-18H along with the spectra after thresholding at η=2.0 (FIGS. 18I-18L), at η=2.1 (FIGS. 18M-18P) and at η=2.2 (FIGS. 18Q-18T), respectively. The four image patterns have components of stripes and a disc. Each image is of size 64�64 pixels, and zoomed by a factor of 4 in both dimensions ease of viewing. In FIG. 18A, there are four stripes, each of which are of 2 pixels wide. These stripes are tilted by -15�, 0�, 15�, and 30� relative to horizontal. FIGS. 18B is the overlap of a disc on the background image of FIG. 18A. FIG. 18D is composed of the superposition of the background (FIG. A) and a star shaped object formed of four stripes, horizontal, vertical, diagonal, all of the width of three pixels and crossed one another at their centers. In FIG. 18C, another disc is overlapped on FIG. 18D by placing it on the center of the star shaped object.
FIG. 19 is a schematic diagram illustrating the method for thresholding the Hough spectra. The mammographic image is divided up into a number of ROIs. For example, for a 512�512 pixel image, 64�64 pixels ROIs may be used. The Hough spectrum is calculated for each ROI (step 1900). The mean and standard deviation of the Hough spectrum for each ROI is also calculated (step 1901) as well as the average mean and standard deviation over all of the ROIs (step 1902). A starting η is chosen (step 1903) and the threshold τ for each spectrum is determined (step 1904). In step 1905, each spectrum is thresholded at the starting η. The number of spectra below the threshold τ is determined (step 1906).
FIGS. 18E-18H show the thresholded Hough spectra of FIGS. 18A-18D, with η=2.6. All four stripes in FIG. 18A are represented by a corresponding group of peak pixels. However the "height" of these peaks are different, caused by the relative strength of the original signal, e.g. the length of stripes. In FIGS. 18K AND 18L, four groups of pixels can be found at the angle near -90�(90�), -45�, 0�, and 45�, reflecting the presence of the star shaped object in FIGS. 18C and 18D, respectively, and they are roughly co-sinusoidal as those stripes which form the star are corradial. The background signal is not as strong as that in FIG. 18I, and the peak for the shortest stripe is even thresholded out. Also, some peak pixels around θ=0� are caused by the "crosstalk" among different objects in the original image, a problem inherited from the traditional Hough transform. This is more obvious in FIG. 18J when the desired signal is weakened further for this reason.
Two experiments were conducted with the application of Hough spectrum technique, one on the detection of spiculated masses and the other on that of architectural distortions. There were 29 mammograms from 16 cases, each containing a spiculated mass, and another 12 mammograms from 6 cases, each with one architectural distortion. Images in both sets of data were of the size 512�512 pixels, and were divided into 64�64 pixel ROIs placed overlappingly with either a horizontal or a vertical shift of 8 pixels. Each ROI was transformed into its Hough spectrum first, and thresholding was conducted on it with the threshold determined according to Eq. (13) and as described with respect to FIGS. 19 and 22. The thresholded ROIs were then classified into two categories to screen out those with strong signals of spiculation as regions of potential lesions.
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS4907156 *Jun 30, 1987Mar 6, 1990University Of ChicagoMethod and system for enhancement and detection of abnormal anatomic regions in a digital imageUS5133020 *Jul 21, 1989Jul 21, 1992Arch Development CorporationAutomated method and system for the detection and classification of abnormal lesions and parenchymal distortions in digital medical imagesUS5260871 *Jul 31, 1991Nov 9, 1993Mayo Foundation For Medical Education And ResearchMethod and apparatus for diagnosis of breast tumorsUS5452367 *Nov 29, 1993Sep 19, 1995Arch Development CorporationAutomated method and system for the segmentation of medical images* Cited by examinerNon-Patent CitationsReference1 *U.S. application No. 07/915,631, Nishikawa et al., filed Jul. 21, 1992.2 *U.S. application No. 08/158,320, Bick et al., filed Nov. 29, 1993.3 *U.S. application No. 08/158,388, Giger et al., filed Nov. 29, 1993.4 *U.S. application No. 08/158,389, Giger et al., filed Nov. 29, 1993.5 *U.S. application No. 08/159,133, Giger et al., filed Nov. 30, 1993.6 *U.S. application No. 08/159,136, Giger et al., filed Nov. 30, 1993.7 *U.S. application No. 08/220,917, Giger et al., filed Mar. 31, 1994.8 *U.S. application No. 08/393,779, Giger et al., filed Feb. 24, 1995.9 *U.S. application No. 08/398,307, Bick et al., filed Mar. 3, 1995.* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS5815591 *Jul 10, 1996Sep 29, 1998R2 Technology, Inc.Method and apparatus for fast detection of spiculated lesions in digital mammogramsUS5984870 *Jul 25, 1997Nov 16, 1999Arch Development CorporationMethod and system for the automated analysis of lesions in ultrasound imagesUS6014452 *Jul 28, 1997Jan 11, 2000R2 Technology, Inc.Method and system for using local attention in the detection of abnormalities in digitized medical imagesUS6035056 *Mar 27, 1997Mar 7, 2000R2 Technology, Inc.Method and apparatus for automatic muscle segmentation in digital mammogramsUS6058322 *Jul 25, 1997May 2, 2000Arch Development CorporationMethods for improving the accuracy in differential diagnosis on radiologic examinationsUS6075879 *Oct 26, 1998Jun 13, 2000R2 Technology, Inc.Method and system for computer-aided lesion detection using information from multiple imagesUS6091841 *Oct 14, 1999Jul 18, 2000Qualia Computing, Inc.Method and system for segmenting desired regions in digital mammogramsUS6115488 *Oct 14, 1999Sep 5, 2000Qualia Computing, Inc.Method and system for combining automated detections from digital mammograms with observed detections of a human interpreterUS6135965 *Dec 2, 1996Oct 24, 2000Board Of Regents, The University Of Texas SystemSpectroscopic detection of cervical pre-cancer using radial basis function networksUS6137898 *Nov 25, 1998Oct 24, 2000Qualia Computing, Inc.Gabor filtering for improved microcalcification detection in digital mammogramsUS6167146 *Oct 14, 1999Dec 26, 2000Qualia Computing, Inc.Method and system for segmentation and detection of microcalcifications from digital mammogramsUS6198838 *Aug 27, 1998Mar 6, 2001R2 Technology, Inc.Method and system for detection of suspicious lesions in digital mammograms using a combination of spiculation and density signalsUS6205236Oct 12, 1999Mar 20, 2001Qualia Computing, Inc.Method and system for automated detection of clustered microcalcifications from digital mammogramsUS6240201Jul 24, 1998May 29, 2001Arch Development CorporationComputerized detection of lung nodules using energy-subtracted soft-tissue and standard chest imagesUS6263092 *Jun 23, 1998Jul 17, 2001R2 Technology, Inc.Method and apparatus for fast detection of spiculated lesions in digital mammogramsUS6317617Jul 25, 1997Nov 13, 2001Arch Development CorporationMethod, computer program product, and system for the automated analysis of lesions in magnetic resonance, mammogram and ultrasound imagesUS6335980Dec 23, 1999Jan 1, 2002Arch Development CorporationMethod and system for the segmentation of lung regions in lateral chest radiographsUS6389157Jan 11, 2001May 14, 2002Qualia Computing, Inc.Joint optimization of parameters for the detection of clustered microcalcifications in digital mammogramsUS6477262Jun 26, 2001Nov 5, 2002Shih-Ping WangComputer-aided diagnosis method and systemUS6516045May 4, 2001Feb 4, 2003The Regents Of The University Of CaliforniaDevice and method for determining proportions of body materialsUS6556699Aug 24, 2001Apr 29, 2003Qualia Computing, Inc.Method for combining automated detections from medical images with observed detections of a human interpreterUS6574357Sep 5, 2001Jun 3, 2003Shih-Ping WangComputer-aided diagnosis method and systemUS6650766Oct 25, 2002Nov 18, 2003Qualia Computing, Inc.Method for combining automated detections from medical images with observed detections of a human interpreterUS6654445Nov 22, 2002Nov 25, 2003Regents Of The University Of CaliforniaDevice and method for determining proportions of body materialsUS6757415Jun 13, 2003Jun 29, 2004Qualia Computing, Inc.Method for determining features from detections in a digital image using a bauer-fisher ratioUS6763128Jun 13, 2003Jul 13, 2004Qualia Computing, Inc.Method for analyzing detections in a set of digital images using case based normalcy classificationUS6801645Jun 23, 2000Oct 5, 2004Icad, Inc.Computer aided detection of masses and clustered microcalcifications with single and multiple input image context classification strategiesUS6898303Jan 16, 2001May 24, 2005Arch Development CorporationMethod, system and computer readable medium for the two-dimensional and three-dimensional detection of lesions in computed tomography scansUS6901156Feb 2, 2001May 31, 2005Arch Development CorporationMethod, system and computer readable medium for an intelligent search workstation for computer assisted interpretation of medical imagesUS6970587Sep 29, 2003Nov 29, 2005Icad, Inc.Use of computer-aided detection system outputs in clinical practiceUS7043064May 3, 2002May 9, 2006The Board Of Trustees Of The Leland Stanford Junior UniversityMethod for characterizing shapes in medical imagesUS7054473Nov 21, 2001May 30, 2006R2 Technology, Inc.Method and apparatus for an improved computer aided diagnosis systemUS7072498Feb 19, 2002Jul 4, 2006R2 Technology, Inc.Method and apparatus for expanding the use of existing computer-aided detection codeUS7184516 *Dec 12, 2002Feb 27, 2007Konica CorporationDigital phase contrast X-ray radiographing systemUS7184582Mar 8, 2004Feb 27, 2007Arch Development CorporationMethod, system and computer readable medium for an intelligent search workstation for computer assisted interpretation of medical imagesUS7203348 *Jan 18, 2002Apr 10, 2007R2 Technology, Inc.Method and apparatus for correction of mammograms for non-uniform breast thicknessUS7248728 *Mar 11, 2003Jul 24, 2007Fujifilm CorporationAbnormal shadow detecting systemUS7298883 *Dec 1, 2003Nov 20, 2007University Of ChicagoAutomated method and system for advanced non-parametric classification of medical images and lesionsUS7308126Oct 14, 2005Dec 11, 2007Icad, Inc.Use of computer-aided detection system outputs in clinical practiceUS7383237Feb 6, 2006Jun 3, 2008Health Discovery CorporationComputer-aided image analysisUS7400755 *Jun 2, 2005Jul 15, 2008Accuray IncorporatedInverse planning using optimization constraints derived from image intensityUS7418123 *Jul 14, 2003Aug 26, 2008University Of ChicagoAutomated method and system for computerized image analysis for prognosisUS7477766Mar 13, 2006Jan 13, 2009Hologic, IncMethod and apparatus for expanding the use of existing computer-aided detection codeUS7483919Dec 7, 2004Jan 27, 2009Almen LaboratoriesObject based image retrievalUS7630532 *May 2, 2006Dec 8, 2009Hologic, Inc.Method and apparatus for correction of mammograms for non-uniform breast thicknessUS7668358 *Jul 18, 2003Feb 23, 2010Hologic, Inc.Model-based grayscale registration of medical imagesUS7680315 *Jul 18, 2003Mar 16, 2010Hologic, Inc.Facilitating computer-aided detection, comparison, or display of medical imagesUS7693254 *Feb 12, 2007Apr 6, 2010General Electric CompanyX-ray device and image-processing methodUS7711169Jun 9, 2008May 4, 2010Accuray IncorporatedInverse planning using optimization constraints derived from image intensityUS7747076 *Dec 21, 2006Jun 29, 2010Fujifilm CorporationMass segmentation using mirror image of region of interestUS7869563Nov 23, 2005Jan 11, 2011Hologic, Inc.Integrated multi-mode mammography/tomosynthesis x-ray system and methodUS7873198Jun 15, 2006Jan 18, 2011Sutter West Bay HospitalsMethods and apparatus for determining proportions of body materialsUS7936924May 18, 2010May 3, 2011Fujifilm CorporationMass segmentation using mirror image of region of interestUS7949091Feb 3, 2010May 24, 2011Hologic, Inc.Full field mammography with tissue exposure control, tomosynthesis, and dynamic field of view processingUS8086015 *Feb 11, 2010Dec 27, 2011Hologic, Inc.Facilitating computer-aided detection, comparison and/or display of medical images by standardizing images from different sourcesUS8131049Oct 23, 2009Mar 6, 2012Hologic, Inc.Breast tomosynthesis with display of highlighted suspected calcificationsUS8155421Aug 4, 2009Apr 10, 2012Hologic, Inc.Matching geometry generation and display of mammograms and tomosynthesis imagesUS8170320 *Mar 3, 2009May 1, 2012Hologic, Inc.Mammography/tomosynthesis systems and methods automatically deriving breast characteristics from breast x-ray images and automatically adjusting image processing parameters accordinglyUS8175219Nov 29, 2010May 8, 2012Hologic, Inc.Integrated multi-mode mammography/tomosynthesis X-ray system and methodUS8275201Mar 5, 2009Sep 25, 2012Tyco Healthcare Group LpImage enhancement and application functionality for medical and other usesUS8340387 *Mar 23, 2008Dec 25, 2012Three Palm SoftwareFast preprocessing algorithms for digital mammography CAD and workstationUS8340388 *Nov 3, 2009Dec 25, 2012Icad, Inc.Systems, computer-readable media, methods, and medical imaging apparatus for the automated detection of suspicious regions of interest in noise normalized X-ray medical imageryUS8416915May 19, 2011Apr 9, 2013Hologic, Inc.Full field mammography with tissue exposure control, tomosynthesis, and dynamic field of view processingUS8565374May 2, 2012Oct 22, 2013Hologic, Inc.Integrated multi-mode mammography/tomosynthesis x-ray system and methodUS8571174Sep 9, 2011Oct 29, 2013Hologic, Inc.Methods and systems for detecting possible error in patient positionUS8571292Jan 26, 2012Oct 29, 2013Hologic IncBreast tomosynthesis with display of highlighted suspected calcificationsUS8615119Aug 1, 2012Dec 24, 2013Covidien LpImage enhancement and application functionality for medical and other usesUS8712127Mar 13, 2012Apr 29, 2014Hologic, Inc.Matching geometry generation and display of mammograms and tomosynthesis imagesUS8744041Sep 9, 2011Jun 3, 2014Hologic, Inc.Methods and systems for dynamically modifying acquisition parameter during image acquisitionUS8774355 *Jun 30, 2004Jul 8, 2014General Electric CompanyMethod and apparatus for direct reconstruction in tomosynthesis imagingUS8775451Aug 20, 2007Jul 8, 2014Almen Laboratories, Inc.Object based image retrievalUS8787522Oct 5, 2011Jul 22, 2014Hologic, IncUpright x-ray breast imaging with a CT mode, multiple tomosynthesis modes, and a mammography modeUS8831171Apr 5, 2013Sep 9, 2014Hologic, Inc.Full field mammography with tissue exposure control, tomosynthesis, and dynamic field of view processingUS20100158332 *Dec 21, 2009Jun 24, 2010Dan RicoMethod and system of automated detection of lesions in medical imagesUS20100278389 *Jul 30, 2009Nov 4, 2010Industrial Technology Research InstituteMethod for image recombination of a plurality of images and image identification and system for image acquiring and identificationUS20110103673 *Nov 3, 2009May 5, 2011Rosenstengel John ESystems, computer-readable media, methods, and medical imaging apparatus for the automated detection of suspicious regions of interest in noise normalized x-ray medical imageryUS20110103712 *Jan 13, 2010May 5, 2011Samsung Electronics Co., Ltd.Structured grids and graph traversal for image processingUS20130266177 *Sep 14, 2012Oct 10, 2013Stmicroelectronics (Grenoble 2) SasMethod and Device for Detecting an Object in an ImageCN101940478BJul 1, 2010Mar 27, 2013株式会社东芝Mammography apparatus, image processing apparatus, and image processing methodEP0977150A2 *Jul 14, 1999Feb 2, 2000Ge Yokogawa Medical Systems, Ltd.X-ray CT apparatus and image diagnostic apparatusEP1032915A1 *Nov 25, 1998Sep 6, 2000Shih-Ping WangComputer-aided diagnosis system and methodEP2428163A2Sep 9, 2011Mar 14, 2012Hologic Inc.Methods and systems for dynamically modifying acquisition parameter during image acquisitionWO1998043201A1 *Mar 27, 1998Oct 1, 1998R2 Technology IncMethod and apparatus for automatic muscle segmentation in digital mammogramsWO1999005640A1 *Jul 24, 1998Feb 4, 1999Arch Dev CorpMethod and system for the segmentation of lung regions in lateral chest radiographsWO1999063478A1 *Jun 5, 1998Dec 9, 1999R2 Technology IncMethod and apparatus for fast detection of spiculated lesions in digital mammogramsWO2000005678A1 *Jul 21, 1999Feb 3, 2000Arch Dev CorpComputerized detection of lung nodules using energy-subtracted soft-tissue and standard chest imagesWO2000013134A1 *Aug 26, 1999Mar 9, 2000R2 Technology IncMethod and system for detection of suspicious lesions in digital mammogramsWO2005057493A1 *Dec 9, 2004Jun 23, 2005Agency Science Tech & ResMethods and apparatus for binarising imagesWO2006138717A2 *Jun 15, 2006Dec 28, 2006California Pacific Med CenterMethods and apparatus for determining proportions of body materials* Cited by examinerClassifications U.S. Classification378/37, 382/171International ClassificationG06T7/00, A61B6/00, G06F19/00, G06T1/00, G06T5/00Cooperative ClassificationG06T7/0081, G06T2207/10116, G06T2207/20061, G06T7/0012, G06T2207/30096, G06T2207/20132, G06T2207/30068European ClassificationG06T7/00S1, G06T7/00B2Legal EventsDateCodeEventDescriptionJan 13, 2009FPAYFee paymentYear of fee payment: 12Jan 13, 2005FPAYFee paymentYear of fee payment: 8Jun 22, 2001ASAssignmentOwner name: UNITED STATES GOVERNMENT SECRETARY OF THE ARMY, THFree format text: CONFIRMATORY LICENSE;ASSIGNOR:UNIVERSITY OF CHICAGO;REEL/FRAME:011917/0854Effective date: 19940222Free format text: CONFIRMATORY LICENSE;ASSIGNOR:UNIVERSITY OF CHICAGO /AR;REEL/FRAME:011917/0854Feb 8, 2001FPAYFee paymentYear of fee payment: 4Jun 22, 1999CCCertificate of correctionJun 3, 1996ASAssignmentOwner name: NATIONAL INSTITUTES OF HEALTH, THE, MARYLANDFree format text: CONFIRMATORY LICENSE;ASSIGNOR:CHICAGAO, THE UNIVERSITY OF;REEL/FRAME:008063/0189Effective date: 19950426May 30, 1995ASAssignmentOwner name: ARCH DEVELOPMENT CORPORATION, ILLINOISFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:GIGER, MARYELLEN L.;ZHANG, MING;LU, PING;REEL/FRAME:007488/0674Effective date: 19950508RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services