6533b85afe1ef96bd12b984c

RESEARCH PRODUCT

An automatic method for metabolic evaluation of gamma knife treatments

Franco MarlettaOrazio GambinoDavide D’ursoGiorgio Ivan RussoCorrado D’arrigoMaria Carla GilardiMaria Gabriella SabiniMassimo IppolitoRoberto Pirrone 6Salvatore VitabileAlessandro StefanoAlessandro StefanoEdoardo Ardizzone 6

subject

medicine.diagnostic_testComputer sciencebusiness.industrymedicine.medical_treatmentComputer Science (all)PET imagingPattern recognitionLesion volumeRandom walkGamma knifeTheoretical Computer ScienceRadiation therapyBiological target volumeSegmentationBiological target volume Gamma Knife treatment PET imaging Random walk SegmentationPositron emission tomographymedicineSegmentationRadiotherapy treatmentGamma Knife treatmentArtificial intelligenceNoise levelbusinessImage resolution

description

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.

yearjournalcountryeditionlanguage
2015-01-01
10.1007/978-3-319-23231-7_52http://hdl.handle.net/10447/153964