Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023; 26th International C Hayit Greenspan,Anant Madabhushi,Russell Tay

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Microstructure Fingerprinting for?Heterogeneously Oriented Tissue Microenvironmentslate the diffusion-weighted signal to cell size and membrane permeability often require simplifying assumptions such as short gradient pulse and Gaussian phase distribution, leading to tissue features that are not necessarily quantitative. Here, we propose a method to quantify tissue microstructure

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AUA-dE: An Adaptive Uncertainty Guided Attention for?Diffusion MRI Models Estimationpartments that are highly nonlinear and complex, and also require dense sampling in .-space. These problems have been investigated using deep learning based techniques. In existing approaches, the labels were calculated from the fully sampled .-space as the ground truth. However, for some of the dMR

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DeepSOZ: A Robust Deep Model for?Joint Temporal and?Spatial Seizure Onset Localization from?MultichaSOZ, consists of a transformer encoder to generate global and channel-wise encodings. The global branch is combined with an LSTM for temporal seizure detection. In parallel, we employ attention-weighted multi-instance pooling of channel-wise encodings to predict the seizure onset zone. DeepSOZis tra

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0302-9743 e 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. ..The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in

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Simulation of?Arbitrary Level Contrast Dose in?MRI Using an?Iterative Global Transformer Models. Quantitative evaluation indicates that the proposed model performs better than other state-of-the-art methods. We further perform quantitative evaluation on downstream tasks such as dose reduction and tumor segmentation to demonstrate the clinical utility.