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Found 4 papers, 1 papers with code
Advancing Brain Tumor Inpainting with Generative Models
Synthesizing healthy brain scans from diseased brain scans offers a potential solution to address the limitations of general-purpose algorithms, such as tissue segmentation and brain extraction algorithms, which may not effectively handle diseased images.
Unsupervised Brain Tumor Segmentation with Image-based Prompts
Specifically, instead of directly training a model for brain tumor segmentation with a large amount of annotated data, we seek to train a model that can answer the question: is a voxel in the input image associated with tumor-like hyper-/hypo-intensity?
Knowledge Graph Completion Method Combined With Adaptive Enhanced Semantic Information
Translation models tend to ignore the rich semantic information in triads in the process of knowledge graph complementation.
CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
Data augmentation is a widely used strategy that improves the training of CNNs, and the design of the augmentation method for brain lesion segmentation is still an open problem.
