Multiple Instance Learning in Medical Images: A Systematic Review
Author:
Affiliation:
1. Institute for Systems and Computer Engineering, Technology and Science—INESC TEC, Porto, Portugal
2. Applied Computing Center, Federal University of Maranhão (UFMA), São Luis, Brazil
3. University Hospital Centre of Santo António, Porto, Portugal
Funder
National Funds through Portuguese Funding Agency, FCT—Fundacão para a Ciência e a Tecnologia
European Commission
U.K. Research and Innovation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10535495.pdf?arnumber=10535495
Reference52 articles.
1. ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging
2. A Comprehensive Review on Multiple Instance Learning
3. Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between borderline and malignant epithelial ovarian tumors
4. Dual space multiple instance representative learning for medical image classification;Zhang
5. Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential
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