基于创新杂交技术的医学图像分割与分类技术研究

Rajesh Sharma R, Akey Sungheetha
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引用次数: 8

摘要

多年来,医学图像处理的增长正在以惊人的方式增长。各类癌症和其他相关人类问题的发病率不断上升,为生物医学研究的发展铺平了道路。因此,对这些医学图像进行处理和分析对临床诊断具有重要意义。这项工作的重点是使用所提出的混合智能技术对脑肿瘤图像进行有效的分类和实时疾病图像的分割。讨论了医学图像的特征提取、图像分类和分割设计面临的挑战和目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation and classification techniques of medical images using innovated hybridized techniques — a study
Over the years, the growth in medical image processing is increasing in a tremendous manner. The rate of increasing diseases with respect to various types of cancer and other related human problems paves the way for the development in biomedical research. Thus processing and analyzing these medical images is of high importance for clinical diagnosis. This work focuses on performing effective classification of brain tumor images and segmentation of live disease images employing the proposed hybrid intelligent techniques. The challenges and objectives on design of feature extraction, image classification and segmentation for medical images are discussed.
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