Deep Learning-Based CT Image Characteristics and Postoperative Anal Function Restoration for Patients with Complex Anal Fistula.

Journal: Journal of healthcare engineering

PMID: 34367532

Abstract

OBJECTIVE: This study aimed to optimize the CT images of anal fistula patients using a convolutional neural network (CNN) algorithm to investigate the anal function recovery.

Authors

Lingling Han

Department of Anorectal, Xinhua Hospital, Affiliated Hospital of Dalian University, Dalian 116021, China.
Yue Chen

The College of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China.
Weidong Cheng

School of Traditional Chinese Medicine, Southern Medical University, Guangzhou 510515, PR China. Electronic address: chengweidong888@sina.com.
He Bai

Department of Anorectal, Xinhua Hospital, Affiliated Hospital of Dalian University, Dalian 116021, China.
Jian Wang

Veterinary Diagnostic Center, Shanghai Animal Disease Control Center, Shanghai, China.
Miaozhi Yu

Department of Anorectal, Xinhua Hospital, Affiliated Hospital of Dalian University, Dalian 116021, China.

Keywords

Algorithms Deep Learning Humans Neural Networks, Computer Rectal Fistula Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (34367532)

Deep Learning-Based CT Image Characteristics and Postoperative Anal Function Restoration for Patients with Complex Anal Fistula.

Abstract

Authors

Keywords

External Resources

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