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2022 | OriginalPaper | Chapter

25. A Detection Method for Early-Stage Colorectal Cancer Using Dual-Tree Complex Wavelet Packet Transform

Authors : Daigo Takano, Teruya Minamoto

Published in: ITNG 2022 19th International Conference on Information Technology-New Generations

Publisher: Springer International Publishing

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Abstract

The chapter introduces a groundbreaking method for detecting early-stage colorectal cancer using Dual-Tree Complex Wavelet Packet Transform (2D-CWPT) and Principal Component Analysis (PCA). Unlike traditional methods that require extensive labeled data, this approach leverages the directional selectivity of 2D-CWPT to extract features from endoscopic images effectively. The method involves preprocessing endoscopic images, applying 2D-CWPT to capture high-frequency components, and using PCA to diagnose cancer based on the first principal component values. The authors demonstrate the method's effectiveness through preliminary and comparison experiments, highlighting its superior accuracy compared to existing methods. The chapter concludes by discussing the method's limitations and suggesting future directions for improving the detection of early-stage colorectal cancer.
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Metadata
Title
A Detection Method for Early-Stage Colorectal Cancer Using Dual-Tree Complex Wavelet Packet Transform
Authors
Daigo Takano
Teruya Minamoto
Copyright Year
2022
Book
ITNG 2022 19th International Conference on Information Technology-New Generations

Print ISBN: 978-3-030-97651-4

Electronic ISBN: 978-3-030-97652-1

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-030-97652-1_25

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