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Titlebook: Medical Image Computing and Computer Assisted Intervention ? MICCAI 2017; 20th International C Maxime Descoteaux,Lena Maier-Hein,Simon Duch

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發(fā)表于 2025-3-26 21:12:30 | 只看該作者
32#
發(fā)表于 2025-3-27 01:53:33 | 只看該作者
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發(fā)表于 2025-3-27 07:59:33 | 只看該作者
Segmentation of Cortical and Subcortical Multiple Sclerosis Lesions Based on Constrained Partial Volspecially affecting small lesions can be modeled, thus yielding improved lesion segmentation. The proposed method is tested on multiple MR image sequences including 3D MP2RAGE, 3D FLAIR, and 3D DIR. Quantitative evaluation is done by comparison with manual segmentations on a cohort of 39 multiple sclerosis early-stage patients.
34#
發(fā)表于 2025-3-27 10:01:30 | 只看該作者
0302-9743 tional Conference on Medical Image?Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017..The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process.?The papers have been organized i
35#
發(fā)表于 2025-3-27 15:27:08 | 只看該作者
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發(fā)表于 2025-3-27 20:47:29 | 只看該作者
Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detectioning component means, principal directions, and variances, for abnormality detection in images. The results on 4 large publicly available datasets, involving retinopathy and cancer, show that our method outperforms the state of the art.
37#
發(fā)表于 2025-3-28 00:40:29 | 只看該作者
Unsupervised Feature Learning for Endomicroscopy Image Retrievalty between pCLE and histology images. Experiments on a database with 700 pCLE mosaics demonstrate that the proposed method outperforms previous works on pCLE feature learning. Specially, the top-1 accuracy in an eight-class retrieval task is 0.659 which leads to 10% improvement compared with the state-of-the-art method.
38#
發(fā)表于 2025-3-28 03:02:53 | 只看該作者
DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRIaining set. We extensively evaluate DOTE in two challenging tasks: image super-resolution and cross-modality synthesis. The experimental results demonstrate superior performance of our method over other state-of-the-art methods.
39#
發(fā)表于 2025-3-28 08:09:17 | 只看該作者
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