Global adaptive histogram feature network for automatic segmentation of infection regions in CT images

作者全名："Min, Xinren; Liu, Yang; Zhou, Shengjing; Huang, Huihua; Zhang, Li; Gong, Xiaojun; Yang, Dongshan; Wang, Menghao; Yang, Rui; Zhong, Mingyang"

作者地址："[Min, Xinren; Liu, Yang; Zhou, Shengjing; Huang, Huihua; Zhang, Li; Gong, Xiaojun; Yang, Dongshan; Zhong, Mingyang] Southwest Univ, Coll Artificial Intelligence, Chongqing 400715, Peoples R China; [Wang, Menghao] Chongqing Med Univ, Affiliated Hosp 2, Dept Hepatobiliary Surg, Chongqing 40010, Peoples R China; [Yang, Rui] Chongqing Coll Elect Engn, Artificial Intelligence & Big Data Coll, Chongqing 401331, Peoples R China"

通信作者："Zhong, MY (通讯作者)，Southwest Univ, Coll Artificial Intelligence, Chongqing 400715, Peoples R China."

来源：MULTIMEDIA SYSTEMS

ESI学科分类：COMPUTER SCIENCE

WOS号：WOS:001269092400001

JCR分区：Q1

影响因子：3.9

年份：2024

卷号：30

期号：4

开始页：　

结束页：　

文献类型：Article

关键词：COVID-19; Deep learning; Feature learning; Automatic segmentation

摘要："Accurate and timely diagnosis of COVID-like virus is of paramount importance for lifesaving. In this work, deep learning techniques are applied to lung CT image segmentation for accurate disease diagnosis. We discuss the limitations of current diagnostic methods, such as RT-PCR, and highlights the advantages of deep learning, including its ability to automatically learn features and handle complex lesion morphology and texture. We, therefore, propose a novel deep learning framework, GAHFNet, specifically designed for automatic segmentation of COVID-19 lung CT images. The proposed method addresses the challenges in lung CT image segmentation, such as the complex image structure and difficulties of distinguishing COVID-19 pneumonia lesions from other pathologies. We provide the detailed description of the proposed GAHFNet. Finally, comprehensive experiments are carried out to evaluate the performance of GAHFNet, and the proposed method outperforms other traditional and the state-of-the-art methods in various evaluation metrics, demonstrating the effectiveness and the efficiency of the proposed method in this task. GAHFNet is able to facilitate the application of artificial intelligence in COVID-19 diagnosis and achieve accurate automatic segmentation of infected areas in COVID-19 lung CT images."

基金机构：National Training Program of Innovation and Entrepreneurship for Undergraduates

基金资助正文：No Statement Available