3d Pathological Signs Detection And Scoring On CPA CT Lung Scans

Abstract

Chronic Pulmonary Aspergillosis (CPA) is a complex type of fungal infection caused by the Aspergillus fungus that mostly affects people with pre-existing lung lesions or weakened immune systems. Pleural thicknening, fungal balls and cavities visualized on CT scans are used to score the extent and gravity of CPA, in a qualitative manner. This work focuses on the use of deep-learning to improve current standards in localising and scoring CPA signs for longitudinal follow-up. We propose an original framework fully implemented in 3D, combining imaging and time series encoding, to provide activation maps, CPA severity scores and 5-years mortality prediction.