The Computed Tomography (CT) has been developed to combine together the diagnostic capabilities of Radiology and Digital Processing, the latter typically provided by computers. The innovative 256-Slice CT scanner offers the possibility of investigating greater volumes in a shorter amount of time, thus improving performances in terms of image resolution and definition, in particular for vascular structures, and reducing the radiation dose for the patient. The perfusion analysis represents a valid support to assess the effectiveness of the therapies aiming at stopping the vascularization typical of tumour lesions. This could permit to evaluate the possible reduction of the tumour neoangiogenesis even at the early stage, before observing the modifications in size, which occur just at a subsequent stage. PERFEct aims at developing new methodologies based on semi-automatic analysis of a temporal sequence of 3D-TC images, capable to enable quantitative assessments of the effectiveness of treatment for secondary hepatic lesions, through analysing the temporal evolution of some parameters (photometric, geometrical, statistical, etc.) extracted from the Region of Interests (ROIs) of lesion acquired in a short time and manually selected by an expert radiologist. These parameters have to be tracked all over the images acquired throughout the treatment in order to achieve the measures needed to quantify the neoangiogenesis degree and the effectiveness of therapy, accordingly. To this purpose, all the algorithms are conceived for high performance distributed SIMD/MIMD architectures, so to allow even real time 4D image analysis. The project has been partly funded by the Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori - IRST (The Cancer Institute of Romagna).

A. Bevilacqua, D. Barone (In stampa/Attività in corso). Automatic analysis of hepatic PERFusion through the usE of CT-4D image reconstruction (PERFECT).

Automatic analysis of hepatic PERFusion through the usE of CT-4D image reconstruction (PERFECT)

BEVILACQUA, ALESSANDRO;
In corso di stampa

Abstract

The Computed Tomography (CT) has been developed to combine together the diagnostic capabilities of Radiology and Digital Processing, the latter typically provided by computers. The innovative 256-Slice CT scanner offers the possibility of investigating greater volumes in a shorter amount of time, thus improving performances in terms of image resolution and definition, in particular for vascular structures, and reducing the radiation dose for the patient. The perfusion analysis represents a valid support to assess the effectiveness of the therapies aiming at stopping the vascularization typical of tumour lesions. This could permit to evaluate the possible reduction of the tumour neoangiogenesis even at the early stage, before observing the modifications in size, which occur just at a subsequent stage. PERFEct aims at developing new methodologies based on semi-automatic analysis of a temporal sequence of 3D-TC images, capable to enable quantitative assessments of the effectiveness of treatment for secondary hepatic lesions, through analysing the temporal evolution of some parameters (photometric, geometrical, statistical, etc.) extracted from the Region of Interests (ROIs) of lesion acquired in a short time and manually selected by an expert radiologist. These parameters have to be tracked all over the images acquired throughout the treatment in order to achieve the measures needed to quantify the neoangiogenesis degree and the effectiveness of therapy, accordingly. To this purpose, all the algorithms are conceived for high performance distributed SIMD/MIMD architectures, so to allow even real time 4D image analysis. The project has been partly funded by the Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori - IRST (The Cancer Institute of Romagna).
In corso di stampa
2010
A. Bevilacqua, D. Barone (In stampa/Attività in corso). Automatic analysis of hepatic PERFusion through the usE of CT-4D image reconstruction (PERFECT).
A. Bevilacqua; D. Barone
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/91197
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