@inproceedings{44996b8bff6b4453897e4c320688c606,
title = "Automatic Thyroid Ultrasound Image Detection and Classification with Priori Knowledge",
abstract = "Medical ultrasonic imaging technology is currently the preferred method to detect and diagnose benign and malignant thyroid nodules, which is widely used because of their low cost and noninvasive damage to patients. But automatic lesion detection and classification on thyroid ultrasound image is quite challenging due to the poor image quality. To solve the problem, based on popular Faster R-CNN network for natural image detection, a ResAt-Faster R-CNN model was proposed in the paper according to the characteristics of thyroid ultrasound image, the residual module and attention mechanism. The medical prior knowledges such as location and distribution information are further introduced to constrain the model to reduce the interference of surrounding tissues. The experimental results demonstrated that our proposed method was effective in the discrimination of thyroid nodules..",
keywords = "Faster r-cnn, Medical priori- knowledge, Thyroid ultrasound image",
author = "Mengdie Shi and Jianrui Ding and Shili Zhao and Zicheng Huang",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computing Machinery. All rights reserved.; 5th International Conference on Computer Science and Application Engineering, CSAE 2021 ; Conference date: 19-10-2021 Through 21-10-2021",
year = "2021",
month = oct,
day = "19",
doi = "10.1145/3487075.3487166",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
editor = "Ali Emrouznejad",
booktitle = "CSAE 2021 - Proceedings of the 5th International Conference on Computer Science and Application Engineering",
address = "美国",
}