Name
Abstract | ||
|---|---|---|
Recent research on spatial and spatio-temporal model checking provides novel image analysis methodologies, rooted in logical methods for topological spaces. Medical Imaging (MI) is a field where such methods show potential for ground-breaking innovation. Our starting point is SLCS, the Spatial Logic for Closure Spaces -- Closure Spaces being a generalisation of topological spaces, covering also discrete space structures -- and topochecker, a model-checker for SLCS (and extensions thereof). We introduce the logical language ImgQL ("Image Query Language"). ImgQL extends SLCS with logical operators describing distance and region similarity. The spatio-temporal model checker topochecker is correspondingly enhanced with state-of-the-art algorithms, borrowed from computational image processing, for efficient implementation of distancebased operators, namely distance transforms. Similarity between regions is defined by means of a statistical similarity operator, based on notions from statistical texture analysis. We illustrate our approach by means of two examples of analysis of Magnetic Resonance images: segmentation of glioblastoma and its oedema, and segmentation of rectal carcinoma. |
Year | Venue | DocType |
|---|---|---|
2018 | arXiv: Logic in Computer Science | Journal |
Volume | Citations | PageRank |
abs/1811.06065 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabrizio Banci Buonamici | 1 | 0 | 0.34 |
| Gina Belmonte | 2 | 3 | 3.76 |
| Vincenzo Ciancia | 3 | 96 | 10.80 |
| Diego Latella | 4 | 1168 | 113.42 |
| Mieke Massink | 5 | 1095 | 87.58 |