معرفی
Shenjun Zhong is a Research Fellow at Monash Biomedical Imaging, Monash University. His research focuses on advancing medical imaging technologies through deep learning and artificial intelligence, particularly in enhancing low-field MRI image quality via image-to-image translation and synthetic image generation. He is a Chief Investigator in the National Mobile Magnetic Resonance Imaging Network project, collaborating with institutions like the University of Queensland and Hyperfine Inc. His work addresses challenges in clinical MRI applications, including CSF volume measurement accuracy and radiological image quality assessment.
Key research interests include medical imaging, deep learning, multimodal learning, and biomedical engineering. Recent studies explore AI-driven solutions for consistency in brain volume measurements and parameter-efficient fine-tuning of large language models for medical tasks.
Notable contributions include peer-reviewed articles on synthetic MRI image generators, cross-modal pre-training for visual question answering, and latent representations of white matter streamlines. His findings aim to improve accessibility and accuracy of portable MRI systems in clinical settings.
