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Found 5 papers, 4 papers with code
Segment Any Medical Model Extended
To this end, a unified platform helps push the boundary of the foundation model for medical images, facilitating the use, modification, and validation of SAM and its variants in medical image segmentation.
DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images
Automatic segmentation of medical images is a key step for diagnostic and interventional tasks.
MONAI: An open-source framework for deep learning in healthcare
For AI models to be used clinically, they need to be made safe, reproducible and robust, and the underlying software framework must be aware of the particularities (e. g. geometry, physiology, physics) of medical data being processed.
MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images
MONAI Label allows researchers to make incremental improvements to their AI-based annotation application by making them available to other researchers and clinicians alike.
Semi-Automatic Algorithm for Breast MRI Lesion Segmentation Using Marker-Controlled Watershed Transformation
The proposed method achieved an average Dice coefficient of 0. 7808$\pm$0. 1729 and Jaccard index of 0. 6704$\pm$0. 2167.
