Detection and classification of lobular and DCIS (small cell) microcalcifications in digital mammograms

被引：8

作者：

Bottema, MJ

Slavotinek, JP

机构：

[1] Flinders Univ S Australia, Dept Math & Stat, Adelaide, SA 5001, Australia

[2] Cooperat Res Ctr Sensor Signal & Informat Proc, Mawson Lakes, SA 4095, Australia

[3] Flinders Univ S Australia, Med Ctr, Dept Med Imaging, Bedford Pk, SA 5042, Australia

来源：

PATTERN RECOGNITION LETTERS | 2000年 / 21卷 / 13-14期

关键词：

microcalcifications; breast cancer; computer-assisted; screening mammography; detection;

D O I：

10.1016/S0167-8655(00)00083-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Microcalcifications are detected by fitting a model to every location in the mammogram. Model parameters yielding the best fit are used as features for detection and classification. The fraction of true positive (tp) detection is 60% with 1.23 false detections per cm(2). The rate of correct classification is 69%. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：1209 / 1214

页数：6

共 26 条

[1]

ANDERSSON I, 1998, 4 INT WORKSH DIG MAM

[2] ANALYSIS OF CANCERS MISSED AT SCREENING MAMMOGRAPHY [J].