Improvement of MRI-based brain connectome with high-speed and high-precision denoising techniques

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K09920
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Radiation science
• Research Institution: Kyoto University
• Principal Investigator: Oishi Naoya 京都大学, 健康長寿社会の総合医療開発ユニット, 特定講師 (40526878)
• Co-Investigator(Kenkyū-buntansha): 杉原 玄一 京都大学, 医学研究科, 助教 (70402261) ; 藤原 宏志 京都大学, 情報学研究科, 准教授 (00362583) ; 鈴木 崇士 京都大学, 健康長寿社会の総合医療開発ユニット, 特定助教 (10572224)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: GPGPU / ノイズ除去 / コネクトーム / MRI

Outline of Final Research Achievements

A non-local means (NLM) filter has been proposed, which can effectively remove noise with preserving edge in return for computational burden. We have therefore developed an accelerating software of the 3D NLM filter by general-purpose graphics processing units (GPGPU), which enables massively parallel computing. In the study, we applied the software to human and animal brain MRI and demonstrated that it is useful for brain connectome which has been innovating in recent years.

Free Research Field

医用画像工学