Computer-assisted image analysis of histopathological breast cancer images using step-DTOCS

被引:0
|
作者
Ikonen, Tiia [1 ]
Niska, Harri [1 ]
Braithwaite, Billy [1 ]
Pollanen, Irene [1 ]
Haataja, Keijo [1 ]
Toivanen, Pekka [1 ]
Tolonen, Teemu [2 ]
Isola, Jorma [2 ]
机构
[1] Univ Eastern Finland, Sch Comp Kuopio Campus, POB 1627, FI-70211 Kuopio, Finland
[2] Univ Tampere, Inst Biomed Technol, FI-33520 Tampere, Finland
关键词
breast cancer; feature extraction; classification; DTOCS; neural network;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we address the epidemiology and morphology questions of breast cancer with special focus on different cell features created by lesions. In addition, we provide an insight into feature extraction and classification schemes in the image analysis pipeline. Based on our conducted research work, a novel feature extraction approach, a modification of Distance Transform on Curved Space (DTOCS), is proposed for analysis and classification of breast cancer images. The first experimental results suggest that the Step-DTOCS-based MLP-network is capable of discriminating different cell structures in a respectable way. The obtained results are presented and analyzed, and further research ideas are discussed.
引用
收藏
页码:187 / 192
页数:6
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