This past academic year three undergraduate students participated in the undergraduate research scholars (URS) program with MIMRTL. Here are more details about their projects: Analysis of Probabilistic Classifiers for Disease Detection in Medical Imaging Camilla Appiani Project Description: The medical field is constantly growing with regards to new applications of artificial intelligence and machine learning. …
Dr. McMillan presented at the 2022 Statistics in Medical Imaging (SMI) Conference that occurred May 25-27th at Vanderbilt University Medical Center. This meeting is the official meeting of the Statistics in Imaging Section of the American Statistical Association and focuses on statistical work in imaging sciences. Dr. McMillan gave a talk entitled “Robustness (or not) …
A hearty congratulations to our MIMRTL team members who graduated in May 2022! Graduating team members include: Matthew Parker, BS, Computer Science Helena Van Hemmen, BS, Applied Mathematics, Engineering, and Physics Zeming Xie, MS, Electrical and Computer Engineering Maribel Torres-Velázquez, PhD, Biomedical Engineering
Dr. McMillan presented at the 2022 International Society for Magnetic Resonance in Medicine (ISMRM) Conference in London, UK on May 7th, 2022. The ISMRM meeting brings together experts all across the world to present new research and provide educational opportunities for scientists and clinicians working in the magnetic resonance imaging (MRI) field. Dr. McMillan presented …
MIMRTL members Dr. Matthew Spangler-Bickell (alum), Dr. Samuel Hurley, and Dr. Alan McMillan recently published a new paper in the Journal of Nuclear Medicine for motion-robust PET brain image reconstruction. This approach leverages a fully data-driven approach using a ultra-short PET frames (approximately 1 second long) to estimate head motion during a PET scan. This …
Samuel Hurley, Ph.D. (he/him) Hometown: Waukesha, WI, USA Lab Position: Scientist What is your current research area? My background is quantitative neuroimaging, so sequences to map parameters like T1, T2, etc. as well as more advanced techniques to model the microstructure of the brain. A lot of that work focuses on ways to make the …
Congrats to MIMRTL team member, and biomedical engineering PhD candidate, Maribel Torres-Velázquez for being selected as one of the 2021 MIT EECS Rising Stars! MIT EECS Rising Stars is an intensive workshop for women graduate students and postdoctoral fellows who are interested in pursuing academic careers and are top candidates in the fields of electrical …
Xue Li and Dr. Alan B. McMillan just published a new article in the Practical Radiation Oncology journal entitled ‘Synthetic CT Generation from 0.35T MR Images for MR-only Radiation Therapy Planning Using Perceptual Loss Models’. This study aimed to synthesize CT images from 0.35T MR-Linac images, and treatment plans in the liver region, for MR-only …
MIMRTL team members just published a new article in the Journal of Digital Imaging entitled ‘Robustifying Deep Networks for Medical Image Segmentation’. This study investigated the robustness of UNets for brain tumor segmentation, in subjects with low- and high-grade gliomas, with respect to nearly unnoticeable adversarial perturbations, and suggest new methods to make these networks …
Hamsalekha Premkumar (she/her) M.S. in Electrical Engineering Hometown: Bangalore, India Twitter: @HamsalekhaPrem1 LinkedIn: @hamsalekha-p Hamsalekha graduated with a MS in electrical engineering. Her research focused on radiomics-based machine learning analysis to distinguish between different types of musculoskeletal lesions and characterize the effect of inmmunotherapy on MRI data of patients with brain metastases. …