Development of cell image data analysis method for highly accurate 3D vesicle movement detection based on computer vision techniques

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K15753
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 43040:Biophysics-related
• Research Institution: The University of Tokyo
• Principal Investigator: Lee Seohyun 東京大学, 定量生命科学研究所, 特任助教 (00847973)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 細胞内物質輸送 / 小胞 / イメージ処理

Outline of Final Research Achievements

This research aimed to acquire three-dimensional trajectory data of intracellular vesicles in living cells at the nanoscale and to elucidate their motion with high precision. In conventional studies, the positions of cells and intracellular organelles could be accurately captured using advanced imaging techniques, but there was an issue of errors occurring during the stage of calculating actual positions from the image data. With the image processing algorithm proposed in this study, the accuracy of image mapping was achieved at the nanoscale by applying linear coordinate transformation to two images obtained from the dual-focus optical system used for calculating three-dimensional coordinates, particularly. Furthermore, we developed software capable of performing such image processing and calculating the final three-dimensional coordinates at once.

Free Research Field

生物物理学

Academic Significance and Societal Importance of the Research Achievements

がん細胞をはじめとする病気の原因となる細胞を外部の薬剤を利用して制御するためには、細胞内で行われる情報伝達パターンに関する知識が最も重要である。本研究では、細胞内での情報伝達を担当する小胞の運動を解析するため、小胞の３次元軌跡を高精度で得られるアルゴリズムを提案した。そのアルゴリズムによって実験者のマニュアルな操作による測定及び計算の誤差を最小限に抑え、簡単な操作でナノスケール精度の３次元座標データが得られる。したがって、本研究は薬剤開発や関連研究の基礎となる意義を持ち、細胞内での情報の伝達に関するあらゆる研究に貢献できると期待される。