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2020 | OriginalPaper | Chapter

A Computer-Aided Diagnostic System to Detect Polyp in Computed Tomographic Colonography Images

Authors : Xiaoyu Zhan, Jianqiang Li, Yan Pei

Published in: Innovative Computing

Publisher: Springer Singapore

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Abstract

Colorectal cancer is a type of malignant from the intestinal tract. The accurate diagnosis of colorectal polyps can effectively guarantee the life safety of potential patients. There are supervised radionics methods and deep learning methods when determining whether polyps exist. This paper proposes to obtain global features set from computed tomographic colonography (CTC) images by radionics methods and the local features set using deep convolutional neural network simultaneously. Specifically, we use the chaotic evolution algorithm to optimize the parameters in the support vector machine classifier and random forest classifier. Finally, our hybrid method achieved better classification result by random forest classifier on combinational features in which accuracy is 91.318% from the experiment.

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Metadata
Title
A Computer-Aided Diagnostic System to Detect Polyp in Computed Tomographic Colonography Images
Authors
Xiaoyu Zhan
Jianqiang Li
Yan Pei
Copyright Year
2020
Publisher
Springer Singapore
Book
Innovative Computing

Print ISBN: 978-981-15-5958-7

Electronic ISBN: 978-981-15-5959-4

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-5959-4_1

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