BraTS 2021
PulseAugur coverage of BraTS 2021 — every cluster mentioning BraTS 2021 across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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Glioblastoma dataset CFB-GBM v2.0 enhanced with complete GTV segmentations
Researchers have released CFB-GBM v2.0, an expanded dataset for glioblastoma research, now including complete Gross Tumour Volume (GTV) delineations for 264 patients. This dataset, available on The Cancer Imaging Archiv…
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BMDS-Net improves brain tumor segmentation with adaptive fusion and Bayesian calibration
Researchers have developed BMDS-Net, a novel two-stage framework designed for multi-modal brain tumor segmentation using MRI data. This system incorporates adaptive modality fusion and boundary-aware regularization to i…
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New framework unifies active and semi-supervised learning for medical image segmentation
Researchers have developed RegAL, a novel framework that unifies active learning and semi-supervised learning for medical image segmentation. This approach addresses the challenge of limited annotated data in practical …
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New Vision Transformer Synthesizes Contrast-Enhanced Brain MRIs
Researchers have developed AA-ViT, an anatomically aware vision transformer designed to synthesize contrast-enhanced brain MRI scans from pre-contrast images. This method aims to improve tumor localization and diagnosis…
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New RF-HiT model offers efficient medical image segmentation
Researchers have developed RF-HiT, a novel Rectified Flow Hierarchical Transformer designed for efficient and accurate medical image segmentation. This model addresses the computational complexity and latency issues of …
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New diffusion model synthesizes MRI sequences efficiently for medical imaging
Researchers have developed Prob-BBDM, a novel diffusion model for synthesizing MRI sequences from 2D axial slices. This model aims to reduce the resource intensity and time required for acquiring multiple imaging modali…
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New SEMIR framework improves image segmentation for small structures
Researchers have developed SEMIR, a novel representation framework designed to improve the segmentation of small and sparse structures in large-scale images. This method decouples inference from the native image grid by…