Adaptive rest condition potentials: first and second order edge-preserving regularization
Computer Vision and Image Understanding
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Collaborative interactions for medical e-diagnosis
International Journal of High Performance Computing and Networking
Operations on Images Using Quad Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Imaging and Communications in Medicine (DICOM): A Practical Introduction and Survival Guide
Digital Imaging and Communications in Medicine (DICOM): A Practical Introduction and Survival Guide
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The goal of this paper is to present a distributed tool for the medical community. This tool is called VACODIS (VAscular COllaborative teleDIagnosiS) enables to identification and quantification of the potential cardiovascular complications of a patient in a semi-automatic way. The first step consists of producing an automatic detection of cardiovascular abnormalities from Echo-Doppler images. The second step shares in a collaborative and adaptive way images and results from the first step. This sharing eases a collaborative diagnosis. Thus, this method enables multiple distant hospital workers (nurses, practitioners …) to contribute to a collaborative diagnosis in the cardiovascular domain.