Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
MICCAI OMIA11 Workshop & STAGE2 Challenge
The 11th Ophthalmology Image Analysis (OMIA) Workshop and the Structural-Functional Transition in Glaucoma Assessment 2 (STAGE2) Challenge on MICCAI 2024 were successfully held in Marrakech, Morocco.
Two MICCAI 2024 Papers
Here are two papers published by the HDMI Lab team at MICCAI2024.
publications
Open fundus photograph dataset with pathologic myopia recognition and anatomical structure annotation
Published in Scientific Data, 2024
Recommended citation: Fang H, Li F, Wu J, et al. Open fundus photograph dataset with pathologic myopia recognition and anatomical structure annotation[J]. Scientific Data, 2024, 11(1): 99.
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Medsegdiff: Medical image segmentation with diffusion probabilistic model
Published in Medical Imaging with Deep Learning, 2024
Inspired by the success of DPM, we propose MedSegDiff, the first DPM-based model for general medical image segmentation tasks.
Recommended citation: Wu J, Fu R, Fang H, et al. Medsegdiff: Medical image segmentation with diffusion probabilistic model[C]//Medical Imaging with Deep Learning. PMLR, 2024: 1623-1639.
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Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle
Published in IEEE Transactions on Medical Imaging, 2024
We propose a diagnosis-first principle, which is to take disease diagnosis as the criterion to calibrate the inter-observer segmentation uncertainty.
Recommended citation: Wu J, Zhang Y, Fang H, et al. Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle[J]. IEEE Transactions on Medical Imaging, 2024.
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Multi-rater prism: Learning self-calibrated medical image segmentation from multiple raters
Published in Science Bulletin, 2024
We propose a novel neural network framework called Multi-rater Prism (MrPrism) to learn medical image segmentation from multiple labels.
Recommended citation: Wu J, Fang H, Zhu J, et al. Multi-rater prism: Learning self-calibrated medical image segmentation from multiple raters[J]. Science Bulletin, 2024, 69(18): 2906-2919.
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Cache-Driven Spatial Test-Time Adaptation for Cross-Modality Medical Image Segmentation
Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024
We introduce Spatial Test-Time Adaptation (STTA), for the first time considering the integration of inter-slice spatial information from 3D volumes with TTA.
Recommended citation: Li X, Fang H, Wang C, et al. Cache-Driven Spatial Test-Time Adaptation for Cross-Modality Medical Image Segmentation[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2024: 146-156.
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Diffusion-Enhanced Transformation Consistency Learning for Retinal Image Segmentation
Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024
To improve label utilization efficiency in semantic segmentation models, we propose Diffusion-Enhanced Transformation Consistency Learning (termed as DiffTCL), a semi-supervised segmentation approach.
Recommended citation: Li X, Fang H, Liu M, et al. Diffusion-Enhanced Transformation Consistency Learning for Retinal Image Segmentation[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2024: 221-231.
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talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.