IEEE

Federated Learning Model Using CBDPL for Medical Image Segmentation

Abstract: Federated learning (FL) allows hospitals and medical centers to train models without sharing patient data. Instead of sending data to a central server, each institution trains the model ...
GitHub

Conformal Prediction for Image Segmentation Using Morphological Prediction Sets

Visual example of our conformal margin: we build a morphological margin (via dilation) that covers all missed pixels (false negatives). Dataset: WBC In the following image, we have a ground truth mask ...
GitHub

DiffAtlas: GenAI-fying Atlas Segmentation via Image-Mask Diffusion

Accurate medical image segmentation is crucial for precise anatomical delineation. Deep learning models like U-Net have shown great success but depend heavily on large datasets and struggle with ...
IEEE

Semi-Supervised Medical Hyperspectral Image Segmentation Using Adversarial Consistency Constraint Learning and Cross Indication Network

Abstract: Hyperspectral imaging technology is considered a new paradigm for high-precision pathological image segmentation due to its ability to obtain spatial and spectral information of the detected ...