Cancer Cytoplasm Segmentation from Cell Image Based on Transfer Learning

Author:

Sultana Rebeka1ORCID,Horibe Hibiki2ORCID,Murakami Tomoaki2ORCID,Shimizu Ikuko3ORCID

Affiliation:

1. Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, Japan

2. Institute of Agriculture, Division of Animal Life Science, Tokyo University of Agriculture and Technology, Japan

3. Institute of Engineering, Division of Advanced Information Technology & Computer Science, Tokyo University of Agriculture and Technology, Japan

Publisher

ACM

Reference15 articles.

1. Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

2. Prajawal Sinha Mayur Tuteja and Sanjay Saxena. 2020. Medical image segmentation: hard and soft computing approaches. SN Applied Sciences  2 1-8.

3. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems 25.

4. Quan Zhou Xiaofu Wu Suofei Zhang Bin Kang Zongyuan Ge and Longin Jan Latecki. 2022. Contextual ensemble network for semantic segmentation. Pattern Recognition 122.

5. Xiaofei Zhou, Songhe Wu, Ran Shi, Bolun Zheng, Shuai Wang, Haibing Yin, Jiyong Zhang, and Chenggang Yan. 2023. Transformer-based Multi-scale Feature Integration Network for Video Saliency Prediction. In IEEE Transactions on Circuits and Systems for Video Technology.

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