Automated segmentation of CT scans is the first step in the pipeline for the interpretation and identification of potential patholo- gies in human organs. Several methods based on Machine Learning are currently available, even if their precision is still outperformed by med- ical doctors. In this field there are some intrinsic limitations to ML ap- proaches, such as the cost and time to acquire high quality annotated scans for training; a considerably high variability of organs morphol- ogy due to age, health conditions, genetics; acquisition noise. This pa- per outlines a new methodology based on Answer Set Programming, which returns reliable, easy-to-program and explainable interpretations. In particular, we focus on the CT scan analysis and retrieval of tree-like structure, corresponding to main blood vessels (arteries) arrangement. The structure is compared to the knowledge base of vessels contained in anatomy text-books. The mapping of vessels names is computed by an ASP program. This preliminary step produces a robust input to a reasoner for the multi-organ labeling and localization problem.

An asp approach for arteries classification in CT-scans / Fabiano, F.; Dal Palu, A.. - ELETTRONICO. - 2710:(2020), pp. 312-326. ((Intervento presentato al convegno 35th Italian Conference on Computational Logic, CILC 2020 tenutosi a ita nel 2020.

An asp approach for arteries classification in CT-scans

Dal Palu A.
2020

Abstract

Automated segmentation of CT scans is the first step in the pipeline for the interpretation and identification of potential patholo- gies in human organs. Several methods based on Machine Learning are currently available, even if their precision is still outperformed by med- ical doctors. In this field there are some intrinsic limitations to ML ap- proaches, such as the cost and time to acquire high quality annotated scans for training; a considerably high variability of organs morphol- ogy due to age, health conditions, genetics; acquisition noise. This pa- per outlines a new methodology based on Answer Set Programming, which returns reliable, easy-to-program and explainable interpretations. In particular, we focus on the CT scan analysis and retrieval of tree-like structure, corresponding to main blood vessels (arteries) arrangement. The structure is compared to the knowledge base of vessels contained in anatomy text-books. The mapping of vessels names is computed by an ASP program. This preliminary step produces a robust input to a reasoner for the multi-organ labeling and localization problem.
An asp approach for arteries classification in CT-scans / Fabiano, F.; Dal Palu, A.. - ELETTRONICO. - 2710:(2020), pp. 312-326. ((Intervento presentato al convegno 35th Italian Conference on Computational Logic, CILC 2020 tenutosi a ita nel 2020.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2884403
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact