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Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow
Research article (Journal of Digital Imaging, 2021) · cited 43× · AI/ML
Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow
Summary
Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow is a scholarly article[1].
Key Facts
Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow. Retrieved May 24, 2026, from https://4ort.xyz/entity/novel-autosegmentation-spatial-similarity-metrics-capture-the-time-required-to-correct-segmentations-better-than-traditi
MLA“Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/novel-autosegmentation-spatial-similarity-metrics-capture-the-time-required-to-correct-segmentations-better-than-traditi.
BibTeX@misc{4ortxyz_novel-autosegmentation-spatial-similarity-metrics-capture-the-time-required-to-correct-segmentations-better-than-traditi_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow}}, year = {2026}, url = {https://4ort.xyz/entity/novel-autosegmentation-spatial-similarity-metrics-capture-the-time-required-to-correct-segmentations-better-than-traditi}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow — https://4ort.xyz/entity/novel-autosegmentation-spatial-similarity-metrics-capture-the-time-required-to-correct-segmentations-better-than-traditi (retrieved 2026-05-24)
