高级检索
当前位置: 首页 > 详情页

A Novel Deep Model for Biopsy Image Grading

文献详情

资源类型:
WOS体系:

收录情况: ◇ CPCI(ISTP)

机构: [1]School of Automation, Guangdong University of Technology, Guangzhou, 510006, China [2]School of Information Technology, York University, Toronto, ON, M3J1P3, Canada [3]The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
出处:

关键词: biopsy image grading deep learning convolutional neural network sigmoid function histopathological image analysis

摘要:
We propose in this paper a deep learning model based on convolutional neural network (CNN) for biopsy image grading. The model outputs a vector of scores indicating presence or severity of the target histopathological characteristics. Within the model, we first design a 7-layer CNN for feature representation and high level concept extraction. Each biopsy image is expressed as a feature vector through our CNN processor. We then place a sigmoid function into the output layer so as to generate a score for each target characteristic. The proposed model is evaluated on a benchmark dataset and a real biopsy image dataset to show its effectiveness.

基金:
语种:
WOS:
第一作者:
第一作者机构: [1]School of Automation, Guangdong University of Technology, Guangzhou, 510006, China
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:2018 今日访问量:0 总访问量:645 更新日期:2024-07-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 广东省中医院 技术支持:重庆聚合科技有限公司 地址:广州市越秀区大德路111号