Selective synthetic augmentation with HistoGAN for improved histopathology image classification

Author:

Xue YuanORCID,Ye Jiarong,Zhou Qianying,Long L. Rodney,Antani SameerORCID,Xue Zhiyun,Cornwell Carl,Zaino Richard,Cheng Keith C.,Huang Xiaolei

Funder

U.S. National Library of Medicine

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference50 articles.

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3. Bowles, C., Chen, L., Guerrero, R., Bentley, P., Gunn, R., Hammers, A., Dickie, D. A., Hernández, M. V., Wardlaw, J., Rueckert, D., 2018. GAN Augmentation: augmenting training data using generative adversarial networks. arXiv:1810.10863.

4. Brock, A., Donahue, J., Simonyan, K., 2018. Large scale GAN training for high fidelity natural image synthesis. arXiv:1809.11096.

5. Automatic cervical cell segmentation and classification in PAP smears;Chankong;Comput. Methods Programs Biomed.,2014

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