Deepnoid to Present Research on Degenerative Brain Diseases at ISMRM 2025

Medical AI specialist Deepnoid announced on the 5th that it will present three research abstracts at the International Society for Magnetic Resonance in Medicine (ISMRM 2025). This marks an opportunity for Deepnoid to expand its research capabilities in the field of neuroscience diagnostics.

Through the conference, Deepnoid will propose AI-based magnetic resonance imaging analysis technology for the precise diagnosis of degenerative brain diseases such as dementia and Parkinson's disease.

The study titled "Improvement of Cingulum Segmentation Performance through Dual MR Contrast Enhancement" was selected for an Oral Presentation, recognized as a major research achievement at the conference. This result demonstrates the technical excellence and clinical value of the research in the field of neuroscience AI.

Deepnoid will also present research on signal extension of Susceptibility-Weighted Map Imaging (SMWI) in limited regions using deep learning, and research on fast SMWI reconstruction based on a complex Swin Transformer. These are expected to contribute to the commercialization of neuroscience AI solutions.

Professor Donghyun Kim of Yonsei University, who collaborated on the SMWI signal extension study, said, "It has great potential to contribute to the early diagnosis of degenerative brain diseases, especially Parkinson's disease," adding, "We hope it will have a positive impact on the transition to clinical research and commercialization stages."

Deepnoid CEO Woosik Choi explained, "The acceptance of the research abstracts is the result of Deepnoid expanding its research capabilities into the neuroscience AI solution field," and added, "We will focus on conducting research on degenerative brain diseases such as dementia and Parkinson's disease and supporting precise brain disease diagnosis through medical AI solutions."

ISMRM 2025 will be held in Hawaii, USA, from May 10 to 15. It is a global academic event where the latest research on MRI technology and AI-based medical imaging analysis solutions are presented.