Linte explains research findings
Cristian Linte, associate professor, Department of Biomedical Engineering, evaluated the performance of non-rigid registration algorithms in dealing with challenges such as reduced visibility of the surface and increased deformation. His findings suggest that the Gaussian Mixture Model-Finite Element Model method outperforms other methods and that it could be a promising approach for non-rigid liver surface registration between pre- and intra-operative scenarios.
Recommended News
-
November 4, 2024
![A professor standing between two students and in front of a white board, explaining something to the students.]()
Computer Engineering faculty awarded to advance the compilation process in quantum computing
Dr. Sonia Lopez Alarcon has been awarded a prestigious grant from the National Science Foundation's Expanding Capacity in Quantum Information Science and Engineering (ExpandQISE) program.
-
November 1, 2024
![the words AI Cluster Hire Initiative appear ona black background with an orange arrow pointing down to the lower left.]()
Upcoming cluster hires in artificial intelligence solidify RIT as a leader in the field
As RIT continues its drive to become a leader in the higher education artificial intelligence space, more than 40 positions spanning multiple disciplines are expected to be filled as part of the university’s commitment to expand its AI expertise.
-
October 21, 2024
![R I T new research building appears on campus with the city of Rochester New York in the background.]()
Science, engineering, and computing faculty will become research building’s first residents
As the final phase of the new research building is completed, faculty-researchers from three of RIT’s colleges are preparing to be its first residents. They expect to move into the 39,000-square-foot building in the spring semester.
-
October 18, 2024
![Blanca Lapizco-Encinas stands in a blue and white dress in the doorway of a room with glass walls.]()
New micro-technique to differentiate pathogens faster discovered by RIT researcher
RIT researcher Blanca Lapizco-Encinas found new ways to identify those mutations faster. Resurrecting an older theoretical technique that can be used for analyzing pathogens that cause disease, her work could improve how clinicians develop more effective treatments.
