- Investigate possible metrics for identification of information-rich patches in DWI data
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- Discuss about DWI data structure and acquisition protocol to have a better understanding of the information available in DWI datasets (e.g. single shell / multi shell, gradient orientations, b-values)
- Identify possible metrics available to measure similarity (e.g. Mutual Information, Correlation) between datasets
- Investigate the potential of CNN for this type of application
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- Discussed with Lauren and clarified some points on Diffusion Imaging. It also might help me to optimize some of my code.
- Discussed with Mohsen about machine learning and how I might use it for data classification in my project.
- Discussed with Henrik about information-rich patches of information in DWI data, and I learned about his LORDWI approach that could be useful to help me identify relevant information in DWI datasets.
- Attended almost all machine learning events, and got a better understanding of their utility and when it might be useful to use them and when it is not necessary.
- Participated in the tutorial contest.
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