Autofocus Layer for Semantic Segmentation
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404 · see citing works
Fully convolutional networks for semantic segmentation
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The multimodal brain tumor image segmentation benchmark (BRATS)
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Self-citationEfficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
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“(d) Empowering the high-resolution pathway of DeepMedic with adaptive autofocus quickly outperforms the gains from the static second pathway on pelvic scan and brain tumor segmentation except for the enhancing tumor.”
BackgroundMethodInfluentialSelf-citationBrain Tumor Segmentation Using Convolutional Neural Networks in MRI Images
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Attention to Scale: Scale-Aware Semantic Image Segmentation
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Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge
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Context based object categorization: A critical survey
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DeepMedic for Brain Tumor Segmentation
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
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An overview of deep learning in medical imaging focusing on MRI
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- Authors
- Qin, Y., Kamnitsas, K., Ancha, S., Nanavati, J., Cottrell, G., Criminisi, A., & Nori, A.
- Affiliations
- University of California San Diego (US)
- Microsoft Research (United Kingdom) (GB)
- Corresponding author
- Qin, Yao
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 603-611
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2963284331
- Cited by
- 135
- References
- 13
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 16 · 2023: 23 · 2022: 24 · 2021: 26 · 2020: 25 · 2019: 13 · 2018: 3
- FWCI
- 5.05
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- semantic segmentation, multi-scale processing, adaptive receptive field, dilation rate, attention mechanism, parameter sharing, scale invariance, multi-organ segmentation, pelvic CT, brain tumor segmentation, magnetic resonance imaging
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