Automatic Acetowhite Lesion Segmentation via Specular Reflection Removal and Deep Attention Network

Automatic acetowhite lesion segmentation in colposcopy images (cervigrams) is essential in assisting gynecologists for the diagnosis of cervical intraepithelial neoplasia grades and cervical cancer. It can also help gynecologists determine the correct lesion areas for further pathological examinatio...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2021-09, Vol.25 (9), p.3529-3540
Hauptverfasser:	Yue, Zijie, Ding, Shuai, Li, Xiaojian, Yang, Shanlin, Zhang, Youtao
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks attention mechanism AW lesion segmentation Bioinformatics Biopsy Cervical cancer Cervix Colposcopy Deep learning Diagnosis Gynecology Image classification Image color analysis Image processing Image segmentation Lesions Medical imaging Metric space Neural networks Pathology Specular reflection specular reflection removal
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