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Found 3 papers, 2 papers with code
MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled Data
Performance measures are an important tool for assessing and comparing different medical image segmentation algorithms.
MISeval: a Metric Library for Medical Image Segmentation Evaluation
Thus, we propose our open-source publicly available Python package MISeval: a metric library for Medical Image Segmentation Evaluation.
Assessing the Role of Random Forests in Medical Image Segmentation
Our results indicate that random forest approaches are a good alternative to deep convolutional neural networks and, thus, allow the usage of medical image segmentation without a GPU.
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