Dr. Macyszyn is an Assistant Professor-in-Residence in the Department of Neurosurgery and Orthopedics at UCLA. He has studied various neurological disorders over the past ten years, including cerebral vasospasm, imaging phenotypes in brain cancer, and advanced imaging techniques for white matter tractography. More recently, at the University of Pennsylvania, Dr. Macyszyn worked on the application of advanced imaging techniques to brain cancer, correlating advanced neuroimaging phenotypes with proteomics in human gliomas and characterizing edema/infiltration in white matter tissue to improve tractography. He developed a unique algorithm that can predict the region of recurrence in newly diagnosed glioblastoma and modeled the effect of edema on brain tractography, culminating in a clinical package for improved perioperative planning. Currently, Dr. Macyszyn uses his extensive knowledge of image analysis, processing and machine learning at UCLA to develop automated algorithms for spinal image segmentation and create quantitative imaging biomarkers of spinal pathology. Dr. Macyszyn aims to develop specific biomarkers for degenerative lumbar disease to standardize diagnosis and augment treatment selection to improve patient outcomes.
JTEHM, Articles, Published ArticlesMulti-Parameter Ensemble Learning for Automated Vertebral Body Segmentation in Heterogeneously Acquired Clinical MR Images
The development of quantitative imaging biomarkers in medicine requires automatic delineation of relevant anatomical structures using available imaging data. However, this task is complicated in clinical medicine due to the variation in scanning parameters and protocols, even within a single... Read more
Posted on 23 JUN 2017