Abstract. Modality is a key facet in medical image retrieval, as a user is likely interested in only one of e.g. radiology images, flowcharts, and.
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This work presents a multi-disciplinary approach to tackle the classi-fication problem by combining image features, meta-data, textual and referential ...
Multi-disciplinary modality classification for medical images. Viktor Gál1, Illés Solt2. 1Dept. of Applied Mathematics and. Computer Science. Ghent University.
We present a multi-disciplinary approach to tackle the classification problem by combining image features, meta-data, textual and referential information. Our ...
Mar 10, 2023 · Bibliographic details on Multi-disciplinary Modality Classification for Medical Images.
Jul 30, 2020 · Owing to human disease diversity and imaging modalities, it is challenging to classify the medical images compared to non-clinical images. The ...
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Multiple kernel learning based modality classification for medical ...
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We present a multi-disciplinary approach to tackle the classification problem by combining image features, meta-data, textual and referential information. We ...
Jun 29, 2023 · The main goal is to bridge the semantic gap and enhance the classification performance of multi-modal medical images based on the deep learning- ...
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We present a multi-disciplinary approach to tackle the classification ... Multi-disciplinary modality classication for medical images. ... Image CLEF 2011 ...
Feb 10, 2023 · All the participants without contraindications will perform multi-modality medical imaging, including brain MRI, retinal fundus photograph, ...