A team of students from the University of British Columbia Okanagan (UBCO) has made significant strides in imaging technology that promises to enhance early detection methods in both medical and environmental fields. Master’s student Jiatao Zhong guided the team in developing a novel adaptive multiple change point energy-based model segmentation (MEBS) system. This unique and powerful tool may change the way that doctors and scientists detect tumors and wildfires.
The study, titled “Energy-based segmentation methods for images with non-Gaussian noise,” was published in Scientific Reports and can be accessed via DOI 10.1038/s41598-025-09211-8. The student research team, consisting of six passionate and committed undergraduate and graduate students, completely immersed themselves into rigorous coding and testing. They tested thousands of images, even using combinations from medical imaging and satellite imaging systems.
Student-Led Innovation
Jiatao Zhong, who was the lead author of the study, told me that the team is excited to see their contributions. “This project gave us a chance to work on something that can make a real difference,” Zhong stated. His sentiment echoed the whole group’s desire to use their academic insight to address real world, practical challenges.
The overall project was led by Associate Professor Xiaoping Shi of UBCO’s Department of Computer Science, Mathematics, Physics and Statistics. Dr. Shi was especially impressed at how much the students had contributed to the overall process. “Our students played a big role in building and refining this model, and they had a chance to apply it to real-world problems,” he said.
The winning student team consisted of Shiyin Du, Canruo Shen, Yiting Chen, Medha Naidu, and Min Gao. From conceptualizing ideas to preparing the deliverables, they worked side by side, illustrating their artistry and creativity in fostering a collaborative bond.
Real-World Applications
The implications of this research are vast. The MEBS system serves as a testbed for enhancing detection capabilities in all sectors. In medicine, meanwhile, it might allow tumors to be detected at an earlier stage, which in turn would improve survival for patients. In environmental monitoring, this technology enhances early wildfire detection. In the face of climate change, detecting wildfires has never been more essential.
Dr. Shi highlighted the importance of these skills for the students’ future careers: “The skills they gained in programming, data analysis, and applied mathematics will give them an edge in their future careers.”
UBCO is committed to developing innovative solutions that address society’s greatest challenges. This promise shines through in the deep commitment to the blend of classroom learning and hands-on experience.
Collaborative Efforts
We are delighted that Dr. Yuejiao Fu joined forces with Dr. Xiaoping Shi to complete this ground-breaking pilots paper. Their collaboration is a testament to the UBCO team’s innovative interdisciplinary approach. The combination of expertise from faculty members and the enthusiasm of students resulted in a project that not only advances academic research but offers tangible benefits to society.
The study has been attracting outcry in academic circles ever since. It’s a reminder of what student-led research can accomplish with the right support. This accomplishment is a remarkable advance in the field of imaging technology and its transformative applications to areas of pressing need.