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Minimization of annotation work: diagnosis of mammographic masses via active learning

  • Published:2018-05-22 Issue:11 Volume:63 Page:115003
  • ISSN:1361-6560
  • Container-title:Physics in Medicine & Biology
  • language:
  • Short-container-title:Phys. Med. Biol.

Author:

Zhao Yu,Zhang Jingyang,Xie Hongzhi,Zhang Shuyang,Gu LixuORCID

Funder

The Chinese NSFC research fund

The 863-national research fund

The National Key research and development program

The special funding of capital health research and development

Publisher

IOP Publishing

Subject

Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Patient Aware Active Learning for Fine-Grained OCT Classification;2022 IEEE International Conference on Image Processing (ICIP);2022-10-16

2. An Adaptive Low-Rank Modeling-Based Active Learning Method for Medical Image Annotation;IRBM;2021-10

3. Deep Co-Training Active Learning for Mammographic Images Classification;2020 Chinese Automation Congress (CAC);2020-11-06

4. O‐MedAL: Online active deep learning for medical image analysis;WIREs Data Mining and Knowledge Discovery;2020-01-27

5. MedAL: Accurate and Robust Deep Active Learning for Medical Image Analysis;2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA);2018-12
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