Segmentation and Feature Extraction in Medical Imaging: A Systematic Review

被引:88
作者
Chowdhary, Chiranji Lal [1 ]
Acharjya, D. P. [1 ]
机构
[1] Vellore Inst Technol, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India
来源
INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE | 2020年 / 167卷
关键词
Medical Imaging; Fuzzy Segmentation; Feature Extraction; Imaging Modality; Segmentation; PRINCIPLES;
D O I
10.1016/j.procs.2020.03.179
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image processing techniques being crucial towards analyzing and resolving issues in medical imaging since last two decades. Medical imaging is a process or technique to find the inner or outer construction of mortal body. The process observes medicinal diagnosis, analyze illnesses and develop data-sets of normal and abnormal imageries. Medical imaging is divided in two folds such as invisible-light medical imaging and visible-light medical imaging. The second type of medical imaging were can be understood by a common person whereas the first type can be interpreted by a radiologist. Analysis of all these require segmentation and feature extraction. In fact a lot of medical imaging techniques are available but authors restrict survey to tumor detection through mammograms or magnetic resonance imaging. In this paper, authors survey on various segmentation and feature extraction methods in medicinal images used for preprocessing. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页码:26 / 36
页数:11
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