A paper by Yuqiao Yang, a doctoral student in Suzuki Laboratory, has been published in IEEE Access.
Conglaturations!

Yang Y., Sato M., Jin Z., and Suzuki K.: Patch-based Deep-learning Model with Limited Training Dataset for Liver Tumor Segmentation in Contrast-enhanced Hepatic Comput Read more...

Dr. Suzuki has been awarded a research grant as a Principal Investigator for a national research project from JST K Program by Japan Science and Technology Agency (JST). Read more...

Our research accepted by IEEE Access with Yuqiao Yang as first author was introduced in EurekAlert!

MHP-Net: A revolutionary AI model for accurate liver tumor segmentation for diagnosis and Read more...

Our research presented by Shogo Kodera at RSNA 2024 and awarded the Cum Laud Award was featured in “Feature & Article” in EurekAlert!

Cancer diagnosis on your laptop? New a Read more...

Prof. Suzuki has been awarded a research grant as a Principal Investigator from Japan Agency for Medical Research and Development (AMED) for the “Medical Research and Development Programs Focused on Technology Transfers: Development of Advanced Measurement and Analysis Systems (AMED-SENTAN) Read more...

Tenma Morikawa and Taiga Shimano (currently in Fukawa lab) won the Outstanding Student Award in the Department of Information and Communications Engineering in March graduation. Congratulations!
The award is given to students completing their undergraduate’s degree and to students who Read more...

Dr. Suzuki has served as a Session Chair for The 39th Annual AAAI Conference on Artificial Intelligence (AAA-25), held in Philadelphia, United States, from February 25 – March 4, 2025.

Session: Humans and AI 5 Read more...

Dr. Suzuki has served as a Session Chair for SPIE Medical Imaging 2025, held in San Diego, United States, from February 16-20, 2025.

“Session 9: Explainable and Trustworthy AI: Transformers” in the Conference 13406 “Image Processing”
“Session 8: Methods& Read more...

Pengyu presented his research plan, entitled “Towards Self-Supervised Learning Foundation Framework for Tumor Segmentation in Computed Tomography Images” at the research plan presentation in the Department of Information and Communication Engineering on June 12, 2024 and he has won the best p Read more...

Our two papers referenced below received the most prestigious Magna Cum Laude Award and the prestigious Cum Laude Award at RSNA 2024!

RSNA is a top conference in the clinical field of medical imaging with a very narrow acceptance rate of about 25% and attracts top radiologists and medical Read more...