Four Vanderbilt engineering students working in the fields of computer science and electrical and computer engineering won prestigious best paper awards at the 2025 SPIE Medical Imaging conference held Feb. 16-20 in San Diego.
SPIE is the international society for optics and photonics and the week-long conference showcases research, notable speakers, technical events, education and networking. The conference features student paper awards specifically to recognize outstanding papers in development and application of medical imaging and diagnosis. The winning students were from laboratories affiliated with the Vanderbilt Institute in Surgery and Engineering (VISE).
There were nine subconferences within the SPIE Medical Imaging conference this year. Those conference topics were physics of medical imaging; image processing; computer-aided diagnosis; image-guided procedures, robotic interventions, and modeling; image perception, observer performance, and technology assessment; clinical and biomedical imaging; imaging informatics; ultrasonic imaging and tomography; and digital and computational pathology
Numerous papers are presented during each subconference. One is selected from best papers as the single overall best paper of the subconference and the student who is first author receives a Robert F. Wagner All-Conference Best Student Paper Finalist Award. Vanderbilt students who won a RFW best student paper finalist award are:
Electrical and computer engineering student Adam Saunders; SPIE Image Processing subconference. Paper: Vasculature-informed spatial smoothing of white matter functional magnetic resonance imaging. Saunders also received second place in the 3-minute Poster Award.
Electrical and computer engineering undergraduate student Gaurav Rudravaram; SPIE Digital and Computational Pathology subconference. Paper: Identifying cellular neighborhood phenotypes differentiating normal and quiescent Crohn’s disease via MxIF.
Computer science student Yitian Long; SPIE Digital and Computational Pathology subconference. Paper: Towards fine-grained renal vasculature segmentation: full-scale hierarchical learning with FH-Seg.
Computer science graduate student Muyang Li; SPIE Image Perception, Observer Performance, and Technology Assessment subconference. Paper: Dataset distillation in medical imaging: a feasibility study.
In other honors, computer science graduate student Jongyeon Yoon received the Image Processing Student Award for his paper: Tractography enhancement in clinically-feasible diffusion MRI using T1-weighted MRI and anatomical context.
Contact: Lucas Johnson, lucas.l.johnson@vanderbilt.edu