First Order Logic with Fuzzy Semantics for Describing and Recognizing Nerves in Medical Images
Journal:
arXiv
Published Date:
Apr 30, 2025
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.
