In computer Science, to validate the work, we use set of benchmark function and compare the results with previous work. In neuroimaging field, how can I validate my work if there is no previous works?
if there is no previous work, you can refer to the most relevant ones to search for support. you can also use new (independently collected) data to validate your result, even your own data (by splitting halves). Some reviewers in CS or Medical Imaging Processing fields always question your work by raising a question "is there any gold standard to be compared with?" I think it is hard to deal with, but validation using varied parameters (to test the robustness) and rest-retest data sets (reliability) are some ways to deal with those reviewers. I always struggle with this hard question, too.
Dr. Han Zhang, thank you for answering. Actually, I'll generate my own data. In this case, if I cover the following points, is it enough (depending on your experience)?
1. Using two or more methods of data collection in your study.
2. Checking the consistency of findings generated by different data collection methods.
3. Checking out the consistency of different data sources within the same method.
To me, generating data from different methods and checking the consistency of the results is a good way to validate the robustness of your method. Maybe our fields are different, in our field (neuroscience), robustness is not enough, people would like to see that you use some results to show your finding is not from noise. To do so, you may need to test the biological meaning by direct (i.e., by changing the subject's status to see if status changing modulate your result) or indirect ways (i.e., correlation with previously widely-used metrics). These are related to "validity". Hope it helps.
Role of advanced neuroimaging, fluid biomarkers and genetic testing in the assessment of sport-related concussion: a systematic review
Michael McCrea, Timothy Meier, Daniel Huber, [...], Thomas McAllister
Article Role of advanced neuroimaging, fluid biomarkers and genetic ...
Thank you Ms.Azhar. Actually, I followed some points used by Prof.Maxime Descoteaux in his research, such as Robustness to Noise, Angular Resolution, and Effect of some parameters of the proposed algorithm. I'll check the article that you attached above. Thank you again.
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