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In this paper, a novel vesselness measure based on analysis of the Hessian matrix is presented. The larger eigenvalue of the Hessian matrix is used for vessel centerlines detection, while vessel orientations are estimated from the eigenvectors corresponding to the smaller eigenvalue. The vesselness measure combines information from vessel centerlines and orientations over scales to segment retinal...
This paper presents the complete 3D and color wound assessment tool, designed using a simple freely handled digital camera inside the ESCALE project. Combining a 3D model of the captured wound images using uncalibrated vision techniques with unsupervised tissue segmentation, it gives access to enhanced tissue classification and measurement. As a result, the tissue classification is directly mapped...
The tracheo-bronchial tree as part of the lung is part of one of the most important organs of the human body. Even if the recent technical development improved resolution and scan velocity related to computed tomography (CT), it cannot image smaller airways and distally to obstructions, which is a limit in CT images besides real bronchoscopy. In this paper, we demonstrate a new method for thickness-mapped...
Unsupervised methods for automatic vessel segmentation from retinal images are attractive when only small datasets, with associated ground truth markings, are available. We present an unsupervised, curvature-based method for segmenting the complete vessel tree from colour retinal images. The vessels are modeled as trenches and the medial lines of the trenches are extracted using the curvature information...
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