195 / 2019-06-30 15:04:19
Localizing and Identifying Intestinal Metaplasia Based on Deep Learning in Oesophagoscope
Keywords—Early Gastric Cancer; Intestinal metaplasia; Endoscopy; Deep Learning; Semantic Segmentation
全文待审
Cong Wang / Zhengzhou University
娅 李 / The First Affiliated Hospital of Zhengzhou University
建宁 姚 / The First Affiliated Hospital of Zhengzhou University
冰 陈 / The First Affiliated Hospital of Zhengzhou University
家友 宋 / School of Information Engineering
潇楠 杨 / Zhengzhou University
Abstract—Intestinal metaplasia is a precancerous lesion, gastric cancer is a very common malignant tumor, and many people die every year from stomach cancer. Early diagnosis of gastric cancer is critical to reducing patient mortality and overall medical burden. However, traditional endoscopic intestinal metaplasia on the gastric mucosa lacks specific performance. Consequently, subtle changes in precancerous intestinal metaplasia are not obvious limiting diagnostic accuracy. As a clinical computer aid in the diagnosis of early gastric cancer, a deep learning framework model called W-Deeplab was proposed for the identification and localization of intestinal metaplasia lesions. It achieves high-precision semantic segmentation of endoscopic images. As a computer aid to clinicians, it can improve the accuracy and efficiency of intestinal metaplasia diagnosis and reduce misdiagnosis.
重要日期
  • 会议日期

    10月09日

    2019

    10月10日

    2019

  • 07月20日 2019

    初稿截稿日期

  • 10月10日 2019

    注册截止日期

主办单位
Xi’an Jiaotong University
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