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

共 50 条

[41] Computer-aided diagnosis in screening mammography
Bick, U
RADIOLOGE, 1996, 36 (01): : 72 - 80
[42] Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography
Horsch, K
Giger, ML
Vyborny, CJ
Venta, LA
ACADEMIC RADIOLOGY, 2004, 11 (03) : 272 - 280
[43] Perceptual challenges to computer-aided diagnosis
Jiang, Yulei
HUMAN VISION AND ELECTRONIC IMAGING XVII, 2012, 8291
[44] Microcalcification detection system for computer aided diagnosis
Kang, HK
Kim, SM
Ro, YM
CISST '05: PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON IMAGING SCIENCE, SYSTEMS, AND TECHNOLOGY: COMPUTER GRAPHICS, 2005, : 237 - 243
[45] Ultrasonic Multi-Feature Analysis Procedure for Computer-Aided Diagnosis of Solid Breast Lesions
Alam, S. Kaisar
Feleppa, Ernest J.
Rondeau, Mark
Kalisz, Andrew
Garra, Brian S.
ULTRASONIC IMAGING, 2011, 33 (01) : 17 - 38
[46] A Review of Computer-Aided Breast Cancer Diagnosis Using Sequential Mammograms
Loizidou, Kosmia
Skouroumouni, Galateia
Nikolaou, Christos
Pitris, Costas
TOMOGRAPHY, 2022, 8 (06) : 2874 - 2892
[47] A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis
Guo, Zicheng
Xie, Jiping
Wan, Yi
Zhang, Min
Qiao, Liang
Yu, Jiaxuan
Chen, Sijing
Li, Bingxin
Yao, Yongqiang
OPEN LIFE SCIENCES, 2022, 17 (01): : 1600 - 1611
[48] Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses
Hupse, Rianne
Samulski, Maurice
Lobbes, Marc
den Heeten, Ard
Imhof-Tas, Mechli W.
Beijerinck, David
Pijnappel, Ruud
Boetes, Carla
Karssemeijer, Nico
EUROPEAN RADIOLOGY, 2013, 23 (01) : 93 - 100
[49] Computer-aided Classification of Mammographic Masses Using the Deep Learning Technology: A Preliminary Study
Qiu, Yuchen
Yan, Shiju
Tan, Maxine
Cheng, Samuel
Liu, Hong
Zheng, Bin
MEDICAL IMAGING 2016: COMPUTER-AIDED DIAGNOSIS, 2015, 9785
[50] Computer-aided diagnosis of mammographic masses based on a supervised content-based image retrieval approach
Tsochatzidis, Lazaros
Zagoris, Konstantinos
Arikidis, Nikolaos
Karahaliou, Anna
Costaridou, Lena
Pratikakis, Ioannis
PATTERN RECOGNITION, 2017, 71 : 106 - 117

← 1 2 3 4 5 →