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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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樓主: 毛發(fā)
51#
發(fā)表于 2025-3-30 10:33:18 | 只看該作者
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發(fā)表于 2025-3-30 14:18:30 | 只看該作者
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發(fā)表于 2025-3-30 18:02:27 | 只看該作者
4D Infant Cortical Surface Atlas Construction Using Spherical Patch-Based Sparse Representationaper, we build the . firstly covering 6 postnatal years with 11 time points (i.e., 1, 3, 6, 9, 12, 18, 24, 36, 48, 60, and 72 months), based on 339 longitudinal MRI scans from 50 healthy infants. To build the 4D cortical surface atlas, ., we adopt a two-stage groupwise surface registration strategy
54#
發(fā)表于 2025-3-30 21:03:38 | 只看該作者
55#
發(fā)表于 2025-3-31 01:23:29 | 只看該作者
Longitudinal Modeling of Multi-modal Image Contrast Reveals Patterns of Early Brain?Growthc resonance (MR) images as a change over time of white matter intensity relative to gray matter. Such a contrast change manifests in specific patterns in different imaging modalities, suggesting that brain maturation is encoded by appearance changes in multi-modal MRI. In this paper, we explore the
56#
發(fā)表于 2025-3-31 06:50:29 | 只看該作者
Prediction of Brain Network Age and Factors of?Delayed Maturation in Very Preterm Infants-invasive neuroimaging modality that allows for early analysis of an infant’s brain connectivity network (i.e., structural connectome) during the critical period of development shortly after birth. In this paper we present a method to accurately assess delayed brain maturation and then use our metho
57#
發(fā)表于 2025-3-31 09:58:22 | 只看該作者
58#
發(fā)表于 2025-3-31 14:18:54 | 只看該作者
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發(fā)表于 2025-3-31 20:58:14 | 只看該作者
Learning-Based Multi-atlas Segmentation of the Lungs and Lobes in Proton MR Images. Here we propose a novel automated lung and lobe segmentation method for pulmonary MR images. This segmentation method employs prior information of the lungs and lobes extracted from CT in the form of multiple MRI atlases, and adopts a learning-based atlas-encoding scheme, based on random forests,
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