CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm
Summary
CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm is a scholarly article[1].
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CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm. Retrieved May 24, 2026, from https://4ort.xyz/entity/ct-liver-tumor-segmentation-hybrid-approach-using-neutrosophic-sets-fast-fuzzy-c-means-and-adaptive-watershed-algorithm
MLA“CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/ct-liver-tumor-segmentation-hybrid-approach-using-neutrosophic-sets-fast-fuzzy-c-means-and-adaptive-watershed-algorithm.
BibTeX@misc{4ortxyz_ct-liver-tumor-segmentation-hybrid-approach-using-neutrosophic-sets-fast-fuzzy-c-means-and-adaptive-watershed-algorithm_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm}}, year = {2026}, url = {https://4ort.xyz/entity/ct-liver-tumor-segmentation-hybrid-approach-using-neutrosophic-sets-fast-fuzzy-c-means-and-adaptive-watershed-algorithm}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm — https://4ort.xyz/entity/ct-liver-tumor-segmentation-hybrid-approach-using-neutrosophic-sets-fast-fuzzy-c-means-and-adaptive-watershed-algorithm (retrieved 2026-05-24)
