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ISSN Печать: 0278-940X
ISSN Онлайн: 1943-619X
Indexed in
Pattern Classification of Images from Acetic Acid–Based Cervical Cancer Screening: A Review
Краткое описание
Automated analysis of digital cervix images acquired during visual inspection with acetic acid (VIA) is found to be of great help to physicians in diagnosing cervical cancer. Application of 3–5% acetic acid to the cervix turns abnormal lesions white, while normal lesions remain unchanged. Digital images of the cervix can be acquired during VIA procedure and can be analyzed using image-processing algorithms. Three main attributes to be considered for analysis are color, vascular patterns, and lesion margins, which differentiate between normal and abnormal lesions. This paper provides a review of state-of-the-art image analysis methods to process digital images of the cervix, acquired during VIA procedure for cervical cancer screening of classification of abnormal lesions.
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Li Yuexiang, Chen Jiawei, Xue Peng, Tang Chao, Chang Jia, Chu Chunyan, Ma Kai, Li Qing, Zheng Yefeng, Qiao Youlin, Computer-Aided Cervical Cancer Diagnosis Using Time-Lapsed Colposcopic Images, IEEE Transactions on Medical Imaging, 39, 11, 2020. Crossref
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Li Yuexiang, Liu Zhi-Hua, Xue Peng, Chen Jiawei, Ma Kai, Qian Tianyi, Zheng Yefeng, Qiao You-Lin, GRAND: A large-scale dataset and benchmark for cervical intraepithelial Neoplasia grading with fine-grained lesion description, Medical Image Analysis, 70, 2021. Crossref
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Li Yuexiang, Chen Jiawei, Ma Kai, Zheng Yefeng, Feature Library: A Benchmark for Cervical Lesion Segmentation, in Information Processing in Medical Imaging, 12729, 2021. Crossref
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Liu Jun, Peng Yun, Zhang Yingchun, A Fuzzy Reasoning Model for Cervical Intraepithelial Neoplasia Classification Using Temporal Grayscale Change and Textures of Cervical Images During Acetic Acid Tests, IEEE Access, 7, 2019. Crossref