OsteoCAD: Cloud-Edge Framework for Bone Tumor Segmentation

OsteoCAD is an eHealth framework that aims to make deep learning (DL) tools more accessible in clinical environments by overcoming challenges such as a lack of computational power and specialized knowledge. It offers comprehensive DL features, encompassing everything from dataset generation and preprocessing to model training and inference, all through an intuitive interface. To alleviate local hardware limitations, OsteoCAD connects securely to remote GPU resources. Its practicality was confirmed via a case study in Mexico that concentrated on segmenting large bone tumors. Findings indicate that OsteoCAD facilitates DL-based eHealth applications without necessitating extensive technical skills or complicated local setups. This framework is detailed in the paper 'OsteoCAD: A Human-in-the-Loop Cloud-Edge Framework for Bone Tumor Segmentation,' accessible on arXiv in the Computer Vision and Pattern Recognition section, which includes submission history and references. This initiative is part of broader efforts to incorporate AI and DL into medical imaging, especially in settings with limited resources.