First Order Logic with Fuzzy Semantics for Describing and Recognizing Nerves in Medical Images

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Název: First Order Logic with Fuzzy Semantics for Describing and Recognizing Nerves in Medical Images
Autoři: Bloch, Isabelle, Bonnot, Enzo, Gori, Pietro, La Barbera, Giammarco, Sarnacki, Sabine
Přispěvatelé: Gori, Pietro
Zdroj: 2025 IEEE International Conference on Fuzzy Systems (FUZZ). :1-6
Publication Status: Preprint
Informace o vydavateli: IEEE, 2025.
Rok vydání: 2025
Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [SDV.IB] Life Sciences [q-bio]/Bioengineering, FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Logic, Computer Science - Artificial Intelligence, segmentation, Mathematics - Logic, fuzzy semantics, fiber bundles, Logic in Computer Science (cs.LO), Artificial Intelligence (cs.AI), FOS: Mathematics, spatial reasoning, recognition, Logic (math.LO)
Popis: This article deals with the description and recognition of fiber bundles, in particular nerves, in medical images, based on the anatomical description of the fiber trajectories. To this end, we propose a logical formalization of this anatomical knowledge. The intrinsically imprecise description of nerves, as found in anatomical textbooks, leads us to propose fuzzy semantics combined with first-order logic. We define a language representing spatial entities, relations between these entities and quantifiers. A formula in this language is then a formalization of the natural language description. The semantics are given by fuzzy representations in a concrete domain and satisfaction degrees of relations. Based on this formalization, a spatial reasoning algorithm is proposed for segmentation and recognition of nerves from anatomical and diffusion magnetic resonance images, which is illustrated on pelvic nerves in pediatric imaging, enabling surgeons to plan surgery.
Accepted for presentation at the FUZZ-IEEE 2025 conference
Druh dokumentu: Article
Conference object
Popis souboru: application/pdf
DOI: 10.1109/fuzz62266.2025.11152235
DOI: 10.48550/arxiv.2505.00173
Přístupová URL adresa: http://arxiv.org/abs/2505.00173
https://telecom-paris.hal.science/hal-05052868v1
Rights: STM Policy #29
CC BY NC ND
Přístupové číslo: edsair.doi.dedup.....52c86f61dd46ece8c8699a47e71b098c
Databáze: OpenAIRE
Popis
Abstrakt:This article deals with the description and recognition of fiber bundles, in particular nerves, in medical images, based on the anatomical description of the fiber trajectories. To this end, we propose a logical formalization of this anatomical knowledge. The intrinsically imprecise description of nerves, as found in anatomical textbooks, leads us to propose fuzzy semantics combined with first-order logic. We define a language representing spatial entities, relations between these entities and quantifiers. A formula in this language is then a formalization of the natural language description. The semantics are given by fuzzy representations in a concrete domain and satisfaction degrees of relations. Based on this formalization, a spatial reasoning algorithm is proposed for segmentation and recognition of nerves from anatomical and diffusion magnetic resonance images, which is illustrated on pelvic nerves in pediatric imaging, enabling surgeons to plan surgery.<br />Accepted for presentation at the FUZZ-IEEE 2025 conference
DOI:10.1109/fuzz62266.2025.11152235