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  • 2020-01-03

DICE Score vs Radiologist-Visual quantification of Virtual Diffusion Sequences–pitfalls of lesion segmentation-based approach as compared to clinical relevance-based

The performances of image segmentation/translation algorithms are typically evaluated by measuring image similarity metrics like DICE score or SSIM. In some instances, this approach may be counter-productive. In this study, we propose to compare such an approach with more clinical relevance focussed qualitative assessment method for estimating the accuracy of a virtually generated diffusion-weighted (DW) sequences using Generative Adversarial Networks (GAN).

Link to complete publication here: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=dqpMNRUAAAAJ&cstart=20&pagesize=80&citation_for_view=dqpMNRUAAAAJ:4DMP91E08xMC

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