sulci recognition error
Posted: Wed Jul 31, 2019 9:33 pm
Hi,
We’re trying to calculate sulci recognition errors with Morphologist 2015 and have some questions:
We initially ran the pipeline with the default options (SPAM, 2008 models, 3.1 graphs) and then ran the Recognition Error function from the expert options. Our results from this function seem strange after reading other posts on the forum. The results provide only false positive values for each sulcus, with 0 for size, False negative, True positive, and SI error=1 (example attached). The exception is the “unknown” sulcus label returning a value of 35000 for sulci size, and values for false negative, true positive, and SI error. Can this actually use SPAM results as we did?
We’re wondering whether we’re interpreting this wrong or if we are running the analysis incorrectly, but we tried also running the old ANN recognition and got similar results.
Also, how can we interpret the “auto_proba” .csv file for SPAM recognition, particularly the first column, of nodes?
Ultimately, we would like to get results analogous to what was done in the Regis et al. 2011 epilepsy paper.
Many thanks in advance,
We’re trying to calculate sulci recognition errors with Morphologist 2015 and have some questions:
We initially ran the pipeline with the default options (SPAM, 2008 models, 3.1 graphs) and then ran the Recognition Error function from the expert options. Our results from this function seem strange after reading other posts on the forum. The results provide only false positive values for each sulcus, with 0 for size, False negative, True positive, and SI error=1 (example attached). The exception is the “unknown” sulcus label returning a value of 35000 for sulci size, and values for false negative, true positive, and SI error. Can this actually use SPAM results as we did?
We’re wondering whether we’re interpreting this wrong or if we are running the analysis incorrectly, but we tried also running the old ANN recognition and got similar results.
Also, how can we interpret the “auto_proba” .csv file for SPAM recognition, particularly the first column, of nodes?
Ultimately, we would like to get results analogous to what was done in the Regis et al. 2011 epilepsy paper.
Many thanks in advance,