New Data-Driven Tools to Quantify Heterogeneous Microenvironments in Live Cell Images
Project/Area Number |
15K18511
|
Research Category |
Grant-in-Aid for Young Scientists (B)
|
Allocation Type | Multi-year Fund |
Research Field |
Biophysics
|
Research Institution | Hokkaido University |
Principal Investigator |
Taylor Nicholas 北海道大学, 電子科学研究所, 特任助教 (50750824)
|
Project Period (FY) |
2015-04-01 – 2017-03-31
|
Project Status |
Completed (Fiscal Year 2016)
|
Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
|
Keywords | Raman Microscopy / Statistics / Data Science / Live-Cell Imaging / Machine Learning |
Outline of Final Research Achievements |
Raman microscopy provides rich images of living cells. Because Raman signal is inherently weak, care must be taken in its processing and analysis. Here, I focused on precisely and accurately processing contamination in the data so that further analyses provided appropriate characterization.
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Report
(3 results)
Research Products
(4 results)