Dr. Or Perlman
Research work
Our lab explores the molecular mechanisms underlying brain disease and develops methods for early diagnosis and therapy optimization. Specifically, we investigate the use of combining machine learning strategies with fundamental biophysical models of magnetic resonance for the early diagnosis and characterization of neurological diseases. We previously demonstrated the usefulness of this strategy for rapidly generating quantitative biomarker maps of protein and lipid concentrations as well as intracellular pH in a mouse brain-tumor model and translated the method to clinical scanners and human subjects.
Areas of interest & scientific knowledge
Brain Disorders Research
Computational & Theoretical Neuroscience
Imaging Research
Selected Publications
- Perlman et al., "Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning", Nature Biomedical Engineering, 2022. https://www.nature.com/articles/s41551-021-00809-7
- Perlman et al., "An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)", Magnetic Resonance in Medicine, 2022. https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.29173
- Perlman et al., "Redesigned reporter gene for improved proton exchange-based molecular MRI contrast", Scientific Reports, 2020. https://www.nature.com/articles/s41598-020-77576-z
- Perlman et al., "CEST MR‐Fingerprinting: Practical considerations and insights for acquisition schedule design and improved reconstruction", Magnetic Resonance in Medicine, 2020. https://onlinelibrary.wiley.com/doi/10.1002/mrm.27937
- Perlman et al., "Gold/Copper@ Polydopamine nanocomposite for contrast-enhanced dual modal computed tomography–magnetic resonance imaging", ACS Applied Nano Materials, 2019. https://pubs.acs.org/doi/abs/10.1021/acsanm.9b00791
