Visual analysis still represents the gold-standard for CT image interpretation, conveying crucial information regarding the diagnosis and prognosis of lung cancer. This work presents the first automatic approach to quantify and classify the lung tumour heterogeneity based on dynamic contrast enhanced-CT (DCE-CT) image sequences, so as it is performed through visual analysis by expert.

Visual-like classification of lung tumour heterogeneity in DCE-CT sequences

BAIOCCO, SERENA;GAVELLI, GIAMPAOLO;BEVILACQUA, ALESSANDRO
2016

Abstract

Visual analysis still represents the gold-standard for CT image interpretation, conveying crucial information regarding the diagnosis and prognosis of lung cancer. This work presents the first automatic approach to quantify and classify the lung tumour heterogeneity based on dynamic contrast enhanced-CT (DCE-CT) image sequences, so as it is performed through visual analysis by expert.
2016
Atti del V Congresso del Gruppo Nazionale di Bioingegneria (GNB)
31
33
Baiocco, S.; Barone, D.; Gavelli, G.; Bevilacqua, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/538687
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