Christopher F. Beaulieu, Rodney D. Brown, et al.
Magnetic Resonance in Medicine
Lymphoma is one of the most common types of cancer for children (ages 0 to 19). Due to the reduced radiation exposure, PET/MR systems that allow simultaneous PET and MR imaging have become the standard of care for diagnosing cancers and monitoring tumor response to therapy in the pediatric population. In this work, we developed a multimodal deep learning algorithm for automatic pediatric lymphoma detection using PET and MRI. Through innovative designs such as standardized uptake value (SUV) guided tumor candidate generation, location aware classification model learning and weighted multimodal feature fusion, our algorithm can be effectively trained with limited data and achieved superior tumor detection performance over the state-of-the-art in our experiments.
Christopher F. Beaulieu, Rodney D. Brown, et al.
Magnetic Resonance in Medicine
David C. Spellmeyer, William C. Swope
Perspectives in Drug Discovery and Design
Kahn Rhrissorrakrai, Filippo Utro, et al.
bioRxiv
Eric K. Neumann, Dennis Quan
PSB 2006