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Algorithms based on deep learning can improve medical image analysis
For the algorithm training, the participating teams had access to a large annotated PET/CT dataset. All algorithms submitted for the final phase of the competition are based on deep learning methods.
Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...
Connected component labeling (CCL) is a fundamental operation within image processing and computer vision, serving as the backbone for tasks such as object recognition, segmentation, and analysis ...
The ensemble of algorithms is able to detect tumour lesions efficiently and precisely.” Professor Stiefelhagen concluded: “While the performance of the algorithms in image data evaluation partly ...
As a Python library for machine learning, with deliberately limited scope, Scikit-learn is very good. It has a wide assortment of well-established algorithms, with integrated graphics.
Zebra Medical Vision has received a CE mark for its medical image analysis technology. The system uses algorithms to uncover evidence of fatty liver, coronary artery calcium, emphysema and other ...
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