Literature DB >> 18383669

An ellipse-fitting based method for efficient registration of breast masses on two mammographic views.

Jiantao Pu1, Bin Zheng, Joseph Ken Leader, David Gur.   

Abstract

When reading mammograms, radiologists routinely search for and compare suspicious breast lesions identified on two corresponding craniocaudal (CC) and mediolateral oblique (MLO) views. Automatically identifying and matching the same true-positive breast lesions depicted on two views is an important step for developing successful multiview based computer-aided detection (CAD) schemes. The authors developed a method to automatically register breast areas and detect matching strips of interest used to identify the matched mass regions depicted on CC and MLO views. The method uses an ellipse based model to fit the breast boundary contour (skin line) and set a local Cartesian coordinate system for each view. One intersection point between the major/minor axis and the fitted ellipse perimeter passed through breast boundary is selected as the origin and the majoraxis and the minoraxis of the ellipse are used as the two axis of the Cartesian coordinate system. When a mass is identified on one view, the scheme computes its position in the local coordinate system. Then, the distance is mapped onto the local coordinate of the other view. At the end of the mapped distance a registered centerline of the matching strip is created. The authors established an image database that includes 200 test examinations each depicting one verified mass visible on the two views. They tested whether the registered centerline identified on another view can be used to locate the matched mass region. The experiments show that the average distance between the mass region centers and the registered centerlines was +/- 8.3 mm and in 91% of testing cases the registered centerline actually passes through the matched mass regions. A matching strip width of 47 mm was required to achieve 100% sensitivity for the test database. The results demonstrate the feasibility of the proposed method to automatically identify masses depicted on CC and MLO views, which may improve future development of multiview based CAD schemes.

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Year:  2008        PMID: 18383669      PMCID: PMC2288654          DOI: 10.1118/1.2828188

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  16 in total

1.  A regional registration technique for automated interval change analysis of breast lesions on mammograms.

Authors:  S Sanjay-Gopal; H P Chan; T Wilson; M Helvie; N Petrick; B Sahiner
Journal:  Med Phys       Date:  1999-12       Impact factor: 4.071

2.  Improvement of computerized mass detection on mammograms: fusion of two-view information.

Authors:  Sophie Paquerault; Nicholas Petrick; Heang-Ping Chan; Berkman Sahiner; Mark A Helvie
Journal:  Med Phys       Date:  2002-02       Impact factor: 4.071

3.  Computer-aided detection schemes: the effect of limiting the number of cued regions in each case.

Authors:  Bin Zheng; Joseph K Leader; Gordon Abrams; Betty Shindel; Victor Catullo; Walter F Good; David Gur
Journal:  AJR Am J Roentgenol       Date:  2004-03       Impact factor: 3.959

4.  Effect of correlation on combining diagnostic information from two images of the same patient.

Authors:  Bei Liu; Charles E Metz; Yulei Jiang
Journal:  Med Phys       Date:  2005-11       Impact factor: 4.071

5.  The use of 3D surface fitting for robust polyp detection and classification in CT colonography.

Authors:  Tarik A Chowdhury; Paul F Whelan; Ovidiu Ghita
Journal:  Comput Med Imaging Graph       Date:  2006-08-17       Impact factor: 4.790

6.  Multiview-based computer-aided detection scheme for breast masses.

Authors:  Bin Zheng; Joseph K Leader; Gordon S Abrams; Amy H Lu; Luisa P Wallace; Glenn S Maitz; David Gur
Journal:  Med Phys       Date:  2006-09       Impact factor: 4.071

7.  Current status and future directions of computer-aided diagnosis in mammography.

Authors:  Robert M Nishikawa
Journal:  Comput Med Imaging Graph       Date:  2007-03-26       Impact factor: 4.790

8.  Combining two mammographic projections in a computer aided mass detection method.

Authors:  Saskia van Engeland; Nico Karssemeijer
Journal:  Med Phys       Date:  2007-03       Impact factor: 4.071

9.  Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images.

Authors:  F F Yin; M L Giger; K Doi; C E Metz; C J Vyborny; R A Schmidt
Journal:  Med Phys       Date:  1991 Sep-Oct       Impact factor: 4.071

10.  Computer screening of xeromammograms: a technique for defining suspicious areas of the breast.

Authors:  W Hand; J L Semmlow; L V Ackerman; F S Alcorn
Journal:  Comput Biomed Res       Date:  1979-10
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Journal:  Nature       Date:  2020-03-25       Impact factor: 49.962

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Journal:  Acad Radiol       Date:  2009-07-25       Impact factor: 3.173

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