光学相干层析成像
介绍(产科)
乳腺癌
连贯性(哲学赌博策略)
乳房成像
计算机科学
医学物理学
光学层析成像
人工智能
医学
癌症
乳腺摄影术
放射科
物理
内科学
量子力学
作者
Rohan Bareja,Diana Mojahed,Christine P. Hendon
摘要
Optical coherence tomography (OCT) is being investigated as an intraoperative margin assessment tool for breast cancer. In this work, we developed a customized deep convolutional neural network (CNN) for classification of breast cancer in OCT images. Images were acquired with a custom ultrahigh-resolution OCT system and a standard resolution system. We classify healthy tissues such as stroma and adipose tissue, as well as diseased tissue including ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Future work involves increasing representation from different kinds of tumors such as mucinous carcinoma, papillary carcinoma, and phyllodes tumors.
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