Literature DB >> 19632867

Matching breast masses depicted on different views a comparison of three methods.

Bin Zheng1, Jun Tan, Marie A Ganott, Denise M Chough, David Gur.   

Abstract

RATIONALE AND
OBJECTIVES: Computerized determination of optimal search areas on mammograms for matching breast mass regions depicted on two ipsilateral views remains a challenge for developing multiview-based computer-aided detection (CAD) schemes. The purpose of this study was to compare three methods aimed at matching CAD-cued mass regions depicted on two views and the associated impact on CAD performance.
MATERIALS AND METHODS: The three search methods used (1) an annular (fan-shaped) band, (2) a straight strip perpendicular to the estimated centerline, and (3) a mixed search area bound on the chest wall side by a straight line and an annular arc on the nipple side, respectively. An image database of 200 examinations with positive results depicting the masses on two views and 200 examinations with negative results was used for testing. Two performance assessment experiments were conducted. The first investigated the maximum matching sensitivity as a function of the search area size, and the second assessed the change in CAD performance using these three search methods.
RESULTS: To include all 200 paired mass regions within the search areas, maximum widths were 28 and 68 mm for the use of the straight strip and the annular band search methods, respectively. When applying a single-image-based CAD scheme to this image database, 172 masses (86% sensitivity) and 523 false-positive (FP) regions (0.33 per image) were detected and cued. Among the positive findings, 92 were cued by the CAD system on both views, and 80 were cued on only one view. In an attempt to match as many of the 172 CAD-cued masses (true-positive [TP] regions) on two views by incrementally reducing the CAD threshold inside the different search areas, the CAD scheme generated 158 TP-TP paired matches with 14 TP-FP paired matches, 142 TP-TP paired matches with 30 TP-FP paired matches, and 146 TP-TP paired matches with 26 TP-FP paired matches, using the methods involving the straight strip, the annular band, and the mixed search areas, respectively. Using the straight strip search method, the CAD also eliminated 25% of FP regions initially cued by the single-image-based CAD scheme and generated the lowest case-based FP detection rate, namely, 15% less than that generated by the annular band method.
CONCLUSIONS: This study showed that among these three search methods, the straight strip method required a smaller search area and achieved the highest level of CAD performance.

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Year:  2009        PMID: 19632867      PMCID: PMC2763994          DOI: 10.1016/j.acra.2009.05.005

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  14 in total

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Authors:  M Y Sallam; K W Bowyer
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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
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4.  Joint two-view information for computerized detection of microcalcifications on mammograms.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski; Mark A Helvie; Chinatana Paramagul; Jun Ge; Jun Wei; Chuan Zhou
Journal:  Med Phys       Date:  2006-07       Impact factor: 4.071

5.  Finding corresponding regions of interest in mediolateral oblique and craniocaudal mammographic views.

Authors:  Saskia van Engeland; Sheila Timp; Nico Karssemeijer
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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.  A method to improve visual similarity of breast masses for an interactive computer-aided diagnosis environment.

Authors:  Bin Zheng; Amy Lu; Lara A Hardesty; Jules H Sumkin; Christiane M Hakim; Marie A Ganott; David Gur
Journal:  Med Phys       Date:  2006-01       Impact factor: 4.071

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

Authors:  Jiantao Pu; Bin Zheng; Joseph Ken Leader; David Gur
Journal:  Med Phys       Date:  2008-02       Impact factor: 4.071

9.  Computer-aided detection in the United Kingdom National Breast Screening Programme: prospective study.

Authors:  Lisanne A L Khoo; Paul Taylor; Rosalind M Given-Wilson
Journal:  Radiology       Date:  2005-11       Impact factor: 11.105

10.  Computer-aided detection performance in mammographic examination of masses: assessment.

Authors:  David Gur; Jennifer S Stalder; Lara A Hardesty; Bin Zheng; Jules H Sumkin; Denise M Chough; Betty E Shindel; Howard E Rockette
Journal:  Radiology       Date:  2004-09-09       Impact factor: 11.105

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2.  Automatic detection of the nipple in screen-film and full-field digital mammograms using a novel Hessian-based method.

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Authors:  Geert Litjens; Robert Toth; Wendy van de Ven; Caroline Hoeks; Sjoerd Kerkstra; Bram van Ginneken; Graham Vincent; Gwenael Guillard; Neil Birbeck; Jindang Zhang; Robin Strand; Filip Malmberg; Yangming Ou; Christos Davatzikos; Matthias Kirschner; Florian Jung; Jing Yuan; Wu Qiu; Qinquan Gao; Philip Eddie Edwards; Bianca Maan; Ferdinand van der Heijden; Soumya Ghose; Jhimli Mitra; Jason Dowling; Dean Barratt; Henkjan Huisman; Anant Madabhushi
Journal:  Med Image Anal       Date:  2013-12-25       Impact factor: 8.545

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