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Lossy DICOM by thanhcongnguyen170 is a document available to read on EtoBox.

What is Lossy DICOM about?

The study investigates the impact of lossy DICOM conversion on the performance of AI models in digital pathology, specifically focusing on MRXS images of bladder, ovarian, and prostate tissues. While no perceptible differences were found between original and converted images, structural similarity indices indicated they were not identical, leading to significant performance variations in AI models trained on these images. The findings emphasize the need for reevaluation of AI algorithms when using DICOM-con

Author

thanhcongnguyen170

Language

EN