Computer Aided Diagnosis of Mammographic Tissue Using Shapelets in Quaternionic Representation

被引：3

作者：

Apostolopoulos, G. ^{[1
]}

Koutras, A. ^{[1
,2
]}

Christoyianni, I. ^{[1
]}

Dermatas, E. ^{[1
]}

机构：

[1] Univ Patras, Elect & Comp Engn Dept, Wired Commun Lab, Patras 26500, Greece

[2] Tech Educ Inst Western Greece, Informat & Mass Media Dept, Patras, Greece

来源：

XIV MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING 2016 | 2016年 / 57卷

关键词：

Shapelets; quaternion; breast cancer; computer-aided diagnosis (CAD); feature extraction; BREAST-CANCER; MASSES;

D O I：

10.1007/978-3-319-32703-7_45

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper a robust regions-of-suspicion (ROS) diagnosis system on mammograms, recognizing all types of abnormalities is presented and evaluated. A new type of descriptors, based on Shapelet decomposition, estimate the source images that generate the observed ROS in mammograms. The Shapelet decomposition coefficients can be used to efficiently detect ROS areas using a new classifier base on quaternionic representation. Extensive experiments using the Mammographic Image Analysis Society (MIAS) database have shown high recognition accuracy over 86% for all kinds of breast, with less computational cost.

引用

页码：222 / 227

页数：6

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