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Michele Larobina

Publications and source records attributed to Michele Larobina.

3 recordsLinked to original sources

Segmentation of magnetic resonance brain images through discriminant analysis.

Segmentation (tissue classification) of medical images obtained from a magnetic resonance (MR) system is a primary step in most applications of medical image post-processing. This paper describes nonparametric discriminant analysis methods to segment multispectral MR images of the brain. Starting from routinely available spin-lattice relaxation time, spin-spin relaxation time, and proton density weighted images (T1w, T2w, PDw), the proposed family of statistical methods is based on: (i) a transform of the images into components that are statistically independent from each other; (ii) a nonparametric estimate of probability density functions of each tissue starting from a training set; (iii) a classic Bayes 0-1 classification rule. Experiments based on a computer built brain phantom (brainweb) and on eight real patient data sets are shown. A comparison with parametric discriminant analysis is also reported. The capability of nonparametric discriminant analysis in improving brain tissue classification of parametric methods is demonstrated. Finally, an assessment of the role of multispectrality in classifying brain tissues is discussed.

Brain↗

Brain tissue volume changes in relapsing-remitting multiple sclerosis: correlation with lesion load.

The aim of this study was to simultaneously measure in vivo volumes of gray matter (GM), normal white matter (WM), abnormal white matter (aWM), and cerebro-spinal fluid (CSF), and to assess their relationship in 50 patients with relapsing-remitting multiple sclerosis (RR-MS) (age range, 21-59; mean EDSS, 2.5; mean disease duration, 9.9 years), using an unsupervised multiparametric segmentation procedure applied to brain MR studies. Tissue volumes were normalized to total intracranial volume providing corresponding fractional volumes (fGM, faWM, fWM, and fCSF), subsequently corrected for aWM-related segmentation inaccuracies and adjusted to mean patients' age according to age-related changes measured in 54 normal volunteers (NV) (age range 16-70). In MS patients aWM was 23.8 +/- 29.8 ml (range 0.4-138.8). A significant decrease in fGM was present in MS patients as compared to NV (49.5 +/- 3.2% vs 53.3 +/- 2.1%; P < 0.0001), with a corresponding increase in fCSF (13.0 +/- 3.8% vs 9.1 +/- 2.4%; P < 0.0001). No difference could be detected between the two groups for fWM (37.5 +/- 2.6% vs 37.6 +/- 2.2%). faWM correlated inversely with fGM (R = -0.434, P < 0.001 at regression analysis), and directly with fCSF (R = 0.473, P < 0.001), but not with fWM. There was a significant correlation between disease duration and EDSS, while no relationship was found between EDSS or disease duration and fractional volumes. Brain atrophy in RR-MS is mainly related to GM loss, which correlates with faWM. Both measures do not appear to significantly affect EDSS, which correlates to disease duration.

Adult↗

Stereotaxy-based regional brain volumetry applied to segmented MRI: validation and results in deficit and nondeficit schizophrenia.

A method for postprocessing of segmented routine brain MRI studies providing automated definition of major structures (frontal, parietal, occipital, and temporal lobes; cerebellar hemispheres; and lateral ventricles) according to the Talairach atlas is presented. The method was applied to MRI studies from 25 normal subjects (NV), 14 patients with deficit schizophrenia (DS), and 14 with nondeficit schizophrenia (NDS), to evaluate their gray matter and CSF regional volumes. The two patient groups did not differ in mean age at illness onset, duration of illness, severity of psychotic symptoms, or disorganization; DS had more severe avolition and worse social functioning than NDS. For validation purposes, brain structures were manually outlined on original MR images in 10 studies, thus obtaining reference measures. Manual and automated measures were repeated 1 month apart to measure reproducibilities of both methods. The automated method required less than 1 min/operator per study vs more than 30 min for manual assessment. Mean absolute difference per structure between the two techniques was 4.8 ml. Overall reproducibility did not significantly differ between the two methods. In subjects with schizophrenia, a significant decrease in GM and increase in CSF were found. GM loss was confined to frontal and temporal lobes. Lateral ventricles were significantly larger bilaterally in NDS compared to NV and only on the right in NDS compared to DS. The finding of greater structural brain abnormalities in NDS adds to the evidence that deficit schizophrenia does not represent just the more severe end of the schizophrenia continuum.

Adolescent↗