Quantitative MR analysis of caudate abnormalities in pediatric ADHD: Proposal for a diagnostic test

Supervised brain segmentation and classification in diagnostic of Attention-Deficit/Hyperactivity Disorder

“…Figure 1 shows the overview of the the diagnostic test method used in this paper. The obtained results by the fully-automatic method on real data are similar to the manual ones provided in [8].…”

“…In the second column of the second row, some voxels are not classified as caudate, while they should be, according to GT (false negatives). This particular sample slice corresponds to the transition between caudate head and body, where the caudate shape changes abruptly from the rounded head to the elongated body [8].…”

“…The objective of the diagnostic test is to discriminate between MRI volumes corresponding to ADHD and healthy subjects. In [8], authors present a diagnostic test to assist in the diagnosis of ADHD in children based on the ratio rCBV/bCBV. Using the Receiver Operating Characteristic (ROC) curve analysis on the defined ratio, the Optimal Cut-Off Value (OCOV) is estimated as the optimal ra- First, to analyze the significance of the ratio (rCBV/bCBV) in discriminating ADHD and control groups, we performed a Student's t-test (with a threshold of p < 0.05).…”

“…In [8], a manual strategy for internal caudate segmentation was proposed based on a simple geometric criterion. In this work, an automatic internal segmentation to separate caudate head and body parts is used based on learning a classifier based on shape features of the Region of Interest (ROI) [9].…”

“…In this work, an automatic internal segmentation to separate caudate head and body parts is used based on learning a classifier based on shape features of the Region of Interest (ROI) [9]. Moreover, an automatic diagnostic test is evaluated, following the manual test proposed in [8]. Figure 1 shows the overview of the the diagnostic test method used in this paper.…”