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Found 4 papers, 4 papers with code
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image Segmentation
To adapt SAM to medical imaging, existing methods primarily rely on tuning strategies that require extensive data or prior prompts tailored to the specific task, making it particularly challenging when only a limited number of data samples are available.
ConvLoRA and AdaBN based Domain Adaptation via Self-Training
To further boost adaptation, we utilize Adaptive Batch Normalization (AdaBN) which computes target-specific running statistics and use it along with ConvLoRA.
An Ensemble Deep Learning Approach for COVID-19 Severity Prediction Using Chest CT Scans
Chest X-rays have been widely used for COVID-19 screening; however, 3D computed tomography (CT) is a more effective modality.
Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets
To evaluate the generalization of the proposed method, we use four medical datasets and compare its performance with state-of-the-art methods for both classification and segmentation tasks.
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