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Found 4 papers, 3 papers with code
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice.
TSdetector: Temporal-Spatial Self-correction Collaborative Learning for Colonoscopy Video Detection
CNN-based object detection models that strike a balance between performance and speed have been gradually used in polyp detection tasks.
Universal Medical Image Representation Learning with Compositional Decoders
To address these challenges, we have developed a decomposed-composed universal medical imaging paradigm (UniMed) that supports tasks at all levels.
DDSB: An Unsupervised and Training-free Method for Phase Detection in Echocardiography
Accurate identification of End-Diastolic (ED) and End-Systolic (ES) frames is key for cardiac function assessment through echocardiography.
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