Metastatic Liver Cancer Detection by CNN Using Artificial Lesion Images

DOI
  • KONISHI Takaaki
    Graduate School of Computer and Cognitive Sciences, Chukyo University
  • DOMAN Keisuke
    Graduate School of Computer and Cognitive Sciences, Chukyo University
  • NAWANO Shigeru
    International University of Health and Welfare Mita Hospital
  • MEKADA Yoshito
    Graduate School of Computer and Cognitive Sciences, Chukyo University

Bibliographic Information

Other Title
  • 人工的病変画像を用いたCNNによる転移性肝がん検出手法

Search this article

Abstract

<p>The interpretation of liver cancer is visually performed by doctor, but it is time-consuming. Although one of the solutions is to detect the cancer lesion by using a machine learning technique, it requires a massive number of training samples. We thus aim to develop a method to synthesize various artificial cancer images by overlaying real cancer legion on CT images obtained from normal subjects. The method proposed in this paper is for lesion image synthesis considering the size, the shape and the contrast of liver cancer lesion. The synthesized images are used together with real images in order to construct an accurate cancer detector. We evaluated the proposed method through experiments, and confirmed the effectiveness of the proposed method.</p>

Journal

  • Medical Imaging Technology

    Medical Imaging Technology 37 (1), 46-50, 2019-01-25

    The Japanese Society of Medical Imaging Technology

Related Projects

See more

Keywords

Details 詳細情報について

Report a problem

Back to top