Document - VoxLogicA: Voxel-based Logical Analyser

2019

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VoxLogicA: Voxel-based Logical Analyser

Belmonte G., Ciancia V., Latella D., Massink M.

Nuclear Medicine and imaging Model Checking Radiological and Ultrasound Technology glioblastoma radiotherapy Radiology segmentation Medical Imaging Biophysics Spatial Logics

VoxLogicA [1] is a free and open source, multi-platform tool, catering for a novel approach to image segmentation, bringing in ideas from formal methods in software engineering, rapid-development, and declarative programming languages, that have been successful in other domains. In a few lines of code, complex analyses can be specified, translating domain knowledge into logical properties. For instance, in brain tumor segmentation, logical properties encode facts such as ''the oedema touches the tumor'', or ''the tumor contains hyperintense areas; furthermore, very intense areas that are very close to hyperintense ones, are part of the tumor''. Such constraints are extremely effective at filtering noise in automated analysis. The logical core is extended by including imaging primitives, e.g., texture similarity or image normalisation. The language is ''a query language for image analysis''. Its innovation potential can be compared to that of the ''Structured Query Language'' SQL, that revolutionised automated data analysis, by permitting queries on large datasets to be designed by experts of the domain to which the data belongs, instead of computer programmers.

Source: ESMRMB 2019, 36th Annual Scientific Meeting, pp. 417–418, Rotterdam, 3/10/2019-5/10/2019

Publisher: Chapman & Hall; [poi] Springer, New York; [poi] Berlin, Heidelberg, Germania

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BibTeX entry

@inproceedings{oai:it.cnr:prodotti:410606,
	title = {VoxLogicA: Voxel-based Logical Analyser},
	author = {Belmonte G. and Ciancia V. and Latella D. and Massink M.},
	publisher = {Chapman \& Hall; [poi] Springer, New York; [poi] Berlin, Heidelberg, Germania},
	doi = {10.1007/s10334-019-00756-0},
	booktitle = {ESMRMB 2019, 36th Annual Scientific Meeting, pp. 417–418, Rotterdam, 3/10/2019-5/10/2019},
	year = {2019}
}