An automatic method for metabolic evaluation of gamma knife treatments

Salvatore Vitabile, Orazio Gambino, Edoardo Ardizzone, Alessandro Stefano, Roberto Pirrone, Maria Carla Gilardi, Alessandro Stefano, Giorgio Russo, Massimo Ippolito, Corrado D’Arrigo, Davide D’Urso, Franco Marletta, Maria Gabriella Sabini

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)

Abstract

Lesion volume delineation of Positron Emission Tomography images is challenging because of the low spatial resolution and high noise level. Aim of this work is the development of an operator independent segmentation method of metabolic images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Twenty-four cerebral tumors are segmented to evaluate the functional follow-up after Gamma Knife radiotherapy treatment. Experimental results show that the segmentation algorithm is accurate and has real-time performance. In addition, it can reflect metabolic changes useful to evaluate radiotherapy response in treated patients.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages579-589
Number of pages11
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'An automatic method for metabolic evaluation of gamma knife treatments'. Together they form a unique fingerprint.

Cite this