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Displaying 18 results

A pre-trained model for volumetric (3D) segmentation of the spleen from CT image.
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A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data.
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A pre-trained SegResNet model for volumetric (3D) segmentation of the 104 whole body segments.
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A pre-trained model for volumetric (3D) multi-organ segmentation from CT image.
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A pre-trained model for volumetric (3D) detection of the lung lesion from CT image.
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A pre-trained model for the endoscopic inbody classification task.
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A pre-trained model for 3D segmentation of the spleen organ from CT images using DeepEdit.
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A pre-trained model for Nuclei Classification within Haematoxylin & Eosin stained histology images.
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A pre-trained model for segmenting nuclei cells with user clicks/interactions.
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A pre-trained model for the endoscopic tool segmentation task.
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A simultaneous segmentation and classification of nuclei within multitissue histology images based on CoNSeP data.
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A neural architecture search algorithm for volumetric (3D) segmentation of the pancreas and pancreatic tumor from CT image.
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A generative model for creating 3D brain MRI from Gaussian noise based on BraTS dataset.
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A pre-trained model for automated detection of metastases in whole-slide histopathology images.
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A generative model for creating 2D brain MRI axial slices from Gaussian noise based on BraTS dataset.
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VISTA-2D is a comprehensive training and inference pipeline for cell segmentation in imaging applications.
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VISTA-3D is a specialized interactive foundation model for 3D medical imaging.
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A generative model for creating 3D CT from Gaussian noise.
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