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Found 5 papers, 2 papers with code
k-MS: A novel clustering algorithm based on morphological reconstruction
This work proposes a clusterization algorithm called k-Morphological Sets (k-MS), based on morphological reconstruction and heuristics.
Automated recognition of the pericardium contour on processed CT images using genetic algorithms
This work proposes the use of Genetic Algorithms (GA) in tracing and recognizing the pericardium contour of the human heart using Computed Tomography (CT) images.
Machine learning in the prediction of cardiac epicardial and mediastinal fat volumes
The obtained results indicate that it is feasible to predict these fats with a high degree of correlation, thus alleviating the requirement for manual or automatic segmentation of both fat volumes.
Multi-Label Retinal Disease Classification using Transformers
First, a new multi-label retinal disease dataset, the MuReD dataset, is constructed, using a number of publicly available datasets for fundus disease classification.
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Morphological classifiers
Two types of morphological classifiers are proposed in the current work, namely, Morphological k-NN (MkNN) and Morphological Dilation Classifier (MDC), which demonstrate the feasibility of the approach.
