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Electrical Engineering and Systems Science > Image and Video Processing
Title: Automatic classification of prostate MR series type using image content and metadata
(Submitted on 16 Apr 2024)
Abstract: With the wealth of medical image data, efficient curation is essential. Assigning the sequence type to magnetic resonance images is necessary for scientific studies and artificial intelligence-based analysis. However, incomplete or missing metadata prevents effective automation. We therefore propose a deep-learning method for classification of prostate cancer scanning sequences based on a combination of image data and DICOM metadata. We demonstrate superior results compared to metadata or image data alone, and make our code publicly available at this https URL
Submission history
From: Deepa Krishnaswamy [view email][v1] Tue, 16 Apr 2024 20:30:16 GMT (1100kb,D)
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