2025/01/02 by Elhoucine Elfatimi, Elfatimi, Elhoucine, Lahcen Elfatimi +1
Computer Science · Medicine · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Graph Theory and Algorithms #Machine Learning (cs.LG) #Medical Imaging Techniques and Applications
paper · pdf · doi:10.48550/arxiv.2501.02024
openalex publication_date 2025/01/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent advancements in model checking have demonstrated significant potential across diverse applications, particularly in signal and image analysis. Medical imaging stands out as a critical domain where model checking can be effectively applied to design and evaluate robust frameworks. These frameworks facilitate automatic and semi-automatic delineation of regions of interest within images, aiding in accurate segmentation. This paper provides a comprehensive analysis of recent works leveraging spatial logic to develop operators and tools for identifying regions of interest, including tumorous and non-tumorous areas. Additionally, we examine the challenges inherent to spatial model-checking techniques, such as variability in ground truth data and the need for streamlined procedures suitable for routine clinical practice.