Artifact Detection and Restoration in Histology Images With Stain-Style and Structural Preservation

Author:

Ke Jing1ORCID,Liu Kai1ORCID,Sun Yuxiang1ORCID,Xue Yuying1,Huang Jiaxuan2,Lu Yizhou3,Dai Jun4,Chen Yaobing5,Han Xiaodan6,Shen Yiqing7ORCID,Shen Dinggang8ORCID

Affiliation:

1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

2. Dulwich College Shanghai, Shanghai, China

3. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China

4. Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

5. Institute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

6. Department of Anaesthesiology, Zhongshan Hospital, Fudan University, Shanghai, China

7. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

8. School of Biomedical Engineering, ShanghaiTech University, Shanghai, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanghai

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Reference71 articles.

1. Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis

2. YOLOv4: Optimal speed and accuracy of object detection;bochkovskiy;arXiv 2004 10934,2020

3. Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

4. Deep inside convolutional networks: Visualising image classification models and saliency maps;simonyan;arXiv 1312 6034,2013

5. Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages

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