A review of automatic mass detection and segmentation in mammographic images

被引：298

作者：

Oliver, Arnau ^{[1
]}

Freixenet, Jordi ^{[1
]}

Marti, Joan ^{[1
]}

Perez, Elsa ^{[2
]}

Pont, Josep ^{[2
]}

Denton, Erika R. E. ^{[3
]}

Zwiggelaar, Reyer ^{[4
]}

机构：

[1] Univ Girona, Dept Comp Architecture & Technol, Ed P-IV,Campus Montilivi, Girona 17071, Spain

[2] Univ Hosp Josep Trueta, Dept Radiol, Girona 17007, Spain

[3] Norfolk & Norwich Univ Hosp, Dept Breast Imaging, Norwich NR4 7UY, Norfolk, England

[4] Univ Wales, Dept Comp Sci, Aberystwyth SY23 3DB, Dyfed, Wales

来源：

MEDICAL IMAGE ANALYSIS | 2010年 / 14卷 / 02期

关键词：

Digital mammography; Computer-Aided Diagnosis systems; Breast mass detection; Automatic segmentation; FROC analysis; COMPUTER-AIDED DETECTION; BREAST-CANCER DETECTION; FIELD DIGITAL MAMMOGRAPHY; FALSE-POSITIVE REDUCTION; INTERVAL CHANGE ANALYSIS; SCREEN-FILM MAMMOGRAPHY; DUAL SYSTEM APPROACH; MARKOV RANDOM-FIELD; DIGITIZED MAMMOGRAMS; CIRCUMSCRIBED MASSES;

D O I：

10.1016/j.media.2009.12.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this paper is to review existing approaches to the automatic detection and segmentation of masses in mammographic images, highlighting the key-points and main differences between the used strategies. The key objective is to point out the advantages and disadvantages of the Various approaches. In contrast with other reviews which only describe and compare different approaches qualitatively, this review also provides a quantitative comparison. The performance of seven mass detection methods is compared using two different mammographic databases: a public digitised database and a local full-field digital database. The results are given in terms of Receiver Operating Characteristic (ROC) and Free-response Receiver Operating Characteristic (FROC) analysis. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：87 / 110

页数：24

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