Výsledky vyhledávání - "ZHENG Yuchao"

Akademický článek

Image Recognition Method of Cervical Adenocarcinoma in Situ Based on Deep Learning

Autor: LIU Chang, ZHENG Yuchao, XIE Wenqian, LI Chen, LI Xiaohan

Publikováno v: Xiehe Yixue Zazhi, Vol 14, Iss 1, Pp 159-167 (2023)

Objective To construct a pathological image diagnostic model of cervical adenocarcinoma in situ(CAIS) based on deep learning algorithm. Methods Pathological tissue sections of CAIS and normal cervical canal and gland sections of chronic cervicitis st

Externí odkaz: https://doaj.org/article/684edfca49e04c17871582b5b55b15fa

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Multimodal 3D Brain Tumor Segmentation with Adversarial Training and Conditional Random Field

Autor: Jiang, Lan, Zheng, Yuchao, Yu, Miao, Zhang, Haiqing, Aladwani, Fatemah, Perelli, Alessandro

Publikováno v: Medical Image Understanding and Analysis (MIUA), Lecture Notes in Computer Science, Springer, vol. 14859, 2024

Accurate brain tumor segmentation remains a challenging task due to structural complexity and great individual differences of gliomas. Leveraging the pre-eminent detail resilience of CRF and spatial feature extraction capacity of V-net, we propose a

Externí odkaz: http://arxiv.org/abs/2411.14418

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Application of Graph Based Features in Computer Aided Diagnosis for Histopathological Image Classification of Gastric Cancer

Autor: Zhang, Haiqing, Li, Chen, Ai, Shiliang, Chen, Haoyuan, Zheng, Yuchao, Li, Yixin, Li, Xiaoyan, Sun, Hongzan, Huang, Xinyu, Grzegorzek, Marcin

The gold standard for gastric cancer detection is gastric histopathological image analysis, but there are certain drawbacks in the existing histopathological detection and diagnosis. In this paper, based on the study of computer aided diagnosis syste

Externí odkaz: http://arxiv.org/abs/2205.08467

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Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology

Autor: Zheng, Yuchao, Li, Chen, Zhou, Xiaomin, Chen, Haoyuan, Xu, Hao, Li, Yixin, Zhang, Haiqing, Li, Xiaoyan, Sun, Hongzan, Huang, Xinyu, Grzegorzek, Marcin

Background: Breast cancer has the highest prevalence in women globally. The classification and diagnosis of breast cancer and its histopathological images have always been a hot spot of clinical concern. In Computer-Aided Diagnosis (CAD), traditional

Externí odkaz: http://arxiv.org/abs/2204.08311

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