First Order Logic with Fuzzy Semantics for Describing and Recognizing Nerves in Medical Images
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| Title: | First Order Logic with Fuzzy Semantics for Describing and Recognizing Nerves in Medical Images |
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| Authors: | Bloch, Isabelle, Bonnot, Enzo, Gori, Pietro, La Barbera, Giammarco, Sarnacki, Sabine |
| Contributors: | Gori, Pietro |
| Source: | 2025 IEEE International Conference on Fuzzy Systems (FUZZ). :1-6 |
| Publication Status: | Preprint |
| Publisher Information: | IEEE, 2025. |
| Publication Year: | 2025 |
| Subject Terms: | [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) |
| Description: | 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 |
| Document Type: | Article Conference object |
| File Description: | application/pdf |
| DOI: | 10.1109/fuzz62266.2025.11152235 |
| DOI: | 10.48550/arxiv.2505.00173 |
| Access URL: | http://arxiv.org/abs/2505.00173 https://telecom-paris.hal.science/hal-05052868v1 |
| Rights: | STM Policy #29 CC BY NC ND |
| Accession Number: | edsair.doi.dedup.....52c86f61dd46ece8c8699a47e71b098c |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | 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 |
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| DOI: | 10.1109/fuzz62266.2025.11152235 |