| Title: | Quality control, denoising, and data mining of the UK Biobank dataset |
| Lead Institution: | ShanghaiTech University |
| Principal investigator: |
Application 87507
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About
Aims: First, we will design methods to assess the quality of the MRI data, and the data of poor quality will be excluded. Second, we will find out the data that are different from most others, because what makes them different could be interesting. Third, we will develop methods to further clean the MRI data in a way that the signals not reflecting the truth of the brain will be removed, and the cleaned data can be used to discover new knowledge of the brain. Finally, we will study how the brain and other organs affect each other. Scientific rationale: This study will establish methods to automatically exclude the MRI data of poor quality. In addition, the data different from most others will provide us insights for biological and clinical research. The methods for cleaning MRI data can help us to gain more accurate knowledge of the brain. Project duration: 36 months. Public health impact: By gaining more knowledge of the brain as well as the interactions between the brain and other organs cast light on brain disease diagnosis and treatment.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 19781 | Green tea catechin EGCG attenuates hippocampal atrophy and cognitive impairment in obesity via autophagy signaling | Kunyi Huang (+14) | 2026 | npj Science of Food |
Enabling scientific discoveries that improve human health