Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool
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Summary
An efficient evaluation tool for 3D medical image segmentation is proposed using 20 evaluation metrics based on a comprehensive literature review and guidelines for selecting a subset of these metrics that is suitable for the data and the segmentation task are provided.
- Type
- article
- Published
- 2015-08-12
- Cited by
- 2,830
- References
- 82
- Access
- Open access
- OpenAlex
- https://openalex.org/W1909740415
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:18182893
Keywords
Computer science, Segmentation, Metric (unit), Scale-space segmentation, Image segmentation
References
- International Journal of Computational Engineering Research(IJCER)
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- Assessment of Reliability of Multi-site Neuroimaging Via Traveling Phantom Study
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- Algorithms for Clustering Data
- 3D Brain Tumors and Internal Brain Structures Segmentation in MR Images
- Defuzzification of spatial fuzzy sets by feature distance minimization
- Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures
- Brain tumor segmentation based on a hybrid clustering technique
- Measures of the Amount of Ecologic Association Between Species
- Statistical validation of image segmentation quality based on a spatial overlap index.
- Three validation metrics for automated probabilistic image segmentation of brain tumours
- MEASURING AGREEMENT WHEN TWO OBSERVERS CLASSIFY PEOPLE INTO CATEGORIES NOT DEFINED IN ADVANCE
- Extending the rand, adjusted rand and jaccard indices to fuzzy partitions
- A New K Nearest Neighbours Algorithm Using Cell Grids for 3D Scattered Point Cloud
- An Efficient Algorithm for Calculating the Exact Hausdorff Distance
- Objective Criteria for the Evaluation of Clustering Methods
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