结肠NBI内窥镜中单FCN计算机辅助诊断系统的开发

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC) Pub Date : 2023-06-25 DOI:10.1109/ITC-CSCC58803.2023.10212877

Daisuke Katayama, Yongfei Wu, Tetsushi Koide, Toru Tamaki, Shigeto Yoshida, Shin Morimoto, Yuki Okamoto, S. Oka, Shinji Tanaka

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引用次数: 0

摘要

在本文中，我们提出了一个单一的全卷积网络(FCN)，能够指示结肠窄带成像(NBI)内窥镜中计算机辅助诊断(CAD)的详细推理结果。所提出的CAD系统能够实时处理，延迟为0.05秒，每秒20帧，即使对于未放大的图像，也可以检测到80%以上的病变。在具有最高置信水平的像素上的分类结果导致诊断与组织病理学结果的一致性为73%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Development of Computer-Aided Diagnosis System Using Single FCN Capable for Indicating Detailed Inference Results in Colon NBI Endoscopy

In this paper, we propose a single fully convolutional network (FCN) capable of indicating the detailed inference results for Computer-Aided Diagnosis (CAD) in colon Narrow Band Imaging (NBI) endoscopy. The proposed CAD system is capable of real-time processing with a latency of 0.05 seconds and 20 frames per second and can detect more than 80% of lesions even for non-magnified images. Classification results at the pixel with the highest confidence level at resulted in a diagnosis with 73% agreement with histopathologic findings.

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来源期刊

2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)

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