Network Visualization and Pyramidal Feature Comparison for Ablative Treatability Classification Using Digitized Cervix Images

Network Visualization and Pyramidal Feature Comparison for Ablative Treatability Classification Using Digitized Cervix Images

Uterine cervical cancer is a leading cause of women’s mortality worldwide. Cervical tissue ablation is an effective surgical excision of high grade lesions that are determined to be precancerous. Our prior work on the Automated Visual Examination (AVE) method demonstrated a highly effective techniqu...

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Bibliographic Details
Main Authors: Peng Guo, Zhiyun Xue, Jose Jeronimo, Julia C. Gage, Kanan T. Desai, Brian Befano, Francisco García, L. Rodney Long, Mark Schiffman, Sameer Antani
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Journal of Clinical Medicine
Subjects:
cervical cancer
thermal ablation
treatability
deep learning
RetinaNet features
customized CNN
Online Access:https://www.mdpi.com/2077-0383/10/5/953

Internet

https://www.mdpi.com/2077-0383/10/5/953

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