Feb. 23, 2024, 5:46 a.m. | Zhenrong Shen, Manman Fei, Xin Wang, Jiangdong Cai, Sheng Wang, Lichi Zhang, Qian Wang

cs.CV updates on arXiv.org arxiv.org

arXiv:2402.14707v1 Announce Type: new
Abstract: Automatic thin-prep cytologic test (TCT) screening can assist pathologists in finding cervical abnormality towards accurate and efficient cervical cancer diagnosis. Current automatic TCT screening systems mostly involve abnormal cervical cell detection, which generally requires large-scale and diverse training data with high-quality annotations to achieve promising performance. Pathological image synthesis is naturally raised to minimize the efforts in data collection and annotation. However, it is challenging to generate realistic large-size cytopathological images while simultaneously synthesizing visually …

abstract annotations arxiv cancer cancer diagnosis cs.cv current data detection diagnosis diverse image performance quality scale screening stage synthesis systems test training training data type

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