학술논문
3d Pathological Signs Detection And Scoring On CPA CT Lung Scans
Document Type
Conference
Source
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) Biomedical Imaging (ISBI), 2021 IEEE 18th International Symposium on. :82-85 Apr, 2021
Subject
Language
ISSN
1945-8452
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.