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Construction of a dataset for deep learning for pulmonary embolism in 3D V/Q SPECT
This summer internship aims to build an annotated dataset for pulmonary embolism (PE) detection on ventilation/perfusion (V/Q) SPECT scans using diverse and multicenter imaging studies. This involves data cleaning, data categorization, and annotation of perfusion defects consistent with the diagnosis of pulmonary embolism, and then use these data to train and validate diagnostic AI models for automatic segmentation of V/Q SPECT mismatches and classification of PE. The intern will contribute to analysis and results dissemination through a final report and publication.
Faculty Supervisor:
Ran Klein
Student:
Partner:
Jubilant Radiopharma
Discipline:
Computer science
Sector:
Professional, scientific and technical services
University:
University of Ottawa
Program:
Accelerate
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