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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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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