DBP2:UNC:Cortical Thickness Comparison - Revision history

Cvachet: /* Tests on a longitudinal pediatric autism study */

2010-09-18T20:15:02Z

Tests on a longitudinal pediatric autism study

Cvachet at 20:00, 27 August 2010

2010-08-27T20:00:06Z

Cvachet: /* Objective */

2010-08-27T19:58:35Z

Objective

Cvachet: /* Results */

2010-08-27T19:57:00Z

Results

Cvachet: /* Results */

2010-08-27T19:56:48Z

Results

Cvachet: /* Results */

2010-08-27T19:48:27Z

Results

Cvachet: /* Results */

2010-08-27T19:48:09Z

Results

Cvachet at 19:15, 27 August 2010

2010-08-27T19:15:15Z

Cvachet at 19:14, 27 August 2010

2010-08-27T19:14:43Z

Cvachet: /* Results */

2010-08-27T19:14:19Z

Results

← Older revision		Revision as of 20:15, 18 September 2010
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	== Tests on a longitudinal pediatric autism study ==		== Tests on a longitudinal pediatric autism study ==

−	In addition to the FreeSurfer tutorial data, we also tested both tools on a longitudinal autism study of 86 ~~subject~~ aged 2-4 years. FreeSurfer showed a low success rate even with manual interventions (< 40% success without intervention, < 70% success after manual intervention), whereas our ARCTIC tool showed no apparent failures. This comparison is though a bit unfair, as we used a pediatric atlas for ARCTIC, whereas FreeSurfer employed its adult template. Our ongoing efforts to use the ARCTIC segmentation maps as input for FreeSurfer were thus far unsuccessful to raise the overall success rate.	+	In addition to the FreeSurfer tutorial data, we also tested both tools on a longitudinal autism study of 86 subjects aged 2-4 years. FreeSurfer showed a low success rate even with manual interventions (< 40% success without intervention, < 70% success after manual intervention), whereas our ARCTIC tool showed no apparent failures. This comparison is though a bit unfair, as we used a pediatric atlas for ARCTIC, whereas FreeSurfer employed its adult template. Our ongoing efforts to use the ARCTIC segmentation maps as input for FreeSurfer were thus far unsuccessful to raise the overall success rate.

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   Back to [[DBP2:UNC:Cortical_Thickness_Roadmap | UNC Cortical Thickness Roadmap]], [[DBP2:UNC:Regional_Cortical_Thickness_Pipeline | UNC Regional Cortical Thickness Pipeline]]
-__NOTOC__
 == Objective ==

@@ Line 4: / Line 4: @@
 == Objective ==
-We would like to evaluate ARCTIC with state of the art techniques, such as FreeSurfer. Thus a statistical analysis, based on Pearson's correlation, has been completed on FreeSurfer's tutorial dataset which includes 40 adult cases. Test were also performed on a longitudinal autism study of 86 subject aged 2-4 years.
+We would like to evaluate ARCTIC with state of the art techniques, such as FreeSurfer. Thus a statistical analysis, based on Pearson's correlation, has been completed on FreeSurfer's tutorial dataset which includes 40 adult cases. Tests were also performed on a longitudinal autism study of 86 subject aged 2-4 years.
 == Pearson's correlation analysis ==

← Older revision		Revision as of 19:57, 27 August 2010
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	When we consider our own tissue segmentation algorithm and our own parcellation map (blue histogram) ARCTIC and FreeSurfer do not seem to correlate well, except for the parietal lobe. However, using directly FreeSurfer's tissue segmentation (red histogram), the two methods are highly correlated for almost all the lobes (r > 0.75), except the frontal cingulate. This correlation slightly improves (yellow histogram, r > 0.85) when we additionally use FreeSurfer's lobar parcellation in our own cortical thickness computation. The tissue segmentation clearly has a strong impact in the cortical thickness computation. Visual comparisons indicate that both segmentations seem equally appropriate, though FreeSurfer’s tissue segmentation procedure leads to larger white matter regions and a better coverage of gyral white matter in deeply folded areas. This study showed a strong correlation between our cortical thickness method and FreeSurfer's.		When we consider our own tissue segmentation algorithm and our own parcellation map (blue histogram) ARCTIC and FreeSurfer do not seem to correlate well, except for the parietal lobe. However, using directly FreeSurfer's tissue segmentation (red histogram), the two methods are highly correlated for almost all the lobes (r > 0.75), except the frontal cingulate. This correlation slightly improves (yellow histogram, r > 0.85) when we additionally use FreeSurfer's lobar parcellation in our own cortical thickness computation. The tissue segmentation clearly has a strong impact in the cortical thickness computation. Visual comparisons indicate that both segmentations seem equally appropriate, though FreeSurfer’s tissue segmentation procedure leads to larger white matter regions and a better coverage of gyral white matter in deeply folded areas. This study showed a strong correlation between our cortical thickness method and FreeSurfer's.
−
−	~~Furthermore, we applied ARCTIC to a longitudinal autism study in 2-4 year old subjects with considerably improved successful processing rate as compared to FreeSurfer.~~

	See results detailed on [[Media:UNCDBP2_ARCTIC_Freesurfer_Evaluation.xls \| spreadsheet]].		See results detailed on [[Media:UNCDBP2_ARCTIC_Freesurfer_Evaluation.xls \| spreadsheet]].

@@ Line 15: / Line 15: @@
 === Results ===
-When we consider our own tissue segmentation algorithm and our own parcellation map (blue histogram) ARCTIC and FreeSurfer do not seem to correlate well, except for the parietal lobe. However, using directly FreeSurfer's tissue segmentation (red histogram), the two methods are highly correlated for almost all the lobes (r > 0.75), except the frontal cingulate. This correlation slightly improves (yellow histogram, r > 0.85) when we additionally use FreeSurfer's lobar parcellation in our own cortical thickness computation. The tissue segmentation clearly has a strong impact in the cortical thickness computation. Visual comparisons indicate that both segmentations seem equally appropriate, though FreeSurfer’s tissue segmentation procedure leads to larger white matter regions and a better coverage of gyral white matter in deeply folded areas.
+When we consider our own tissue segmentation algorithm and our own parcellation map (blue histogram) ARCTIC and FreeSurfer do not seem to correlate well, except for the parietal lobe. However, using directly FreeSurfer's tissue segmentation (red histogram), the two methods are highly correlated for almost all the lobes (r > 0.75), except the frontal cingulate. This correlation slightly improves (yellow histogram, r > 0.85) when we additionally use FreeSurfer's lobar parcellation in our own cortical thickness computation. The tissue segmentation clearly has a strong impact in the cortical thickness computation. Visual comparisons indicate that both segmentations seem equally appropriate, though FreeSurfer’s tissue segmentation procedure leads to larger white matter regions and a better coverage of gyral white matter in deeply folded areas. This study showed a strong correlation between our cortical thickness method and FreeSurfer's.
-This study showed a strong correlation between our cortical thickness method and FreeSurfer's. Furthermore, we applied ARCTIC to a longitudinal autism study in 2-4 year old subjects with considerably improved successful processing rate as compared to FreeSurfer.
+Furthermore, we applied ARCTIC to a longitudinal autism study in 2-4 year old subjects with considerably improved successful processing rate as compared to FreeSurfer.
 See results detailed on [[Media:UNCDBP2_ARCTIC_Freesurfer_Evaluation.xls | spreadsheet]].

@@ Line 21: / Line 21: @@
 See results detailed on [[Media:UNCDBP2_ARCTIC_Freesurfer_Evaluation.xls | spreadsheet]].
-[[Image:UNCDBP2_ARCTIC_Freesurfer_Evaluation.jpg]]
+[[Image:UNCDBP2_ARCTIC_Freesurfer_Evaluation.jpg|center]]
 == Tests on a longitudinal pediatric autism study ==
 In addition to the  FreeSurfer tutorial data, we also tested both tools on a longitudinal autism study of 86 subject aged 2-4 years. FreeSurfer showed a low success rate even with manual interventions (< 40% success without intervention,  < 70% success after manual intervention), whereas our ARCTIC tool showed no apparent failures. This comparison is though a bit unfair, as we used a pediatric atlas for ARCTIC, whereas FreeSurfer employed its adult template. Our ongoing efforts to use the ARCTIC segmentation maps as input for FreeSurfer were thus far unsuccessful to raise the overall success rate.