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Efficient, high-performance pancreatic segmentation using multi-scale feature extraction

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 نشر من قبل Moritz Knolle
 تاريخ النشر 2020
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For artificial intelligence-based image analysis methods to reach clinical applicability, the development of high-performance algorithms is crucial. For example, existent segmentation algorithms based on natural images are neither efficient in their parameter use nor optimized for medical imaging. Here we present MoNet, a highly optimized neural-network-based pancreatic segmentation algorithm focused on achieving high performance by efficient multi-scale image feature utilization.



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