ABSTRACT
Objective To compare the differences between the schizophrenics with negative and positive symptoms on prefrontal lobe and thalamus by proton magnetic resonance spectroscopy ( 1 H-MRS). Methods 58 negative subtype and 51 positive subtype schizophrenics were examined at prefrontal lobe and thalamus by multivoxel 1H-MRS before antipsychotic treatment The N-acetylaspartate (NAA), choline-containing compounds ( Cho), and creatine compounds (Cr) were measured and the ratios of NAA/Cr, Cho/Cr were determined. Results On right thalamus,the NAA/Cr ratio in negative subtype patients ( 1.40 ± 0.29 ) demonstrated lower than that in positive subtype ( 1.62 ± 0.33 ), the same phenomenon were appeared on male, female, non-first-episode, with-medicine and without-medicine patients (P ＜ 0.05 or 0.01 ). The Cho/Cr ratio on right thalamus in negative subtype of female,non-first-episode,without-medicine schizophrenics were lower than those in positive subtype (P ＜ 0.05 ).On left prefrontal lobe,left thalamus and right thalamus, the NAA/Cr ratios both in negative subtype and positive subtype schizophrenics were significantly negatively related with age of onset(P＜0. 05 or 0.01 ). In negative subtype schizophrenics,the Cho/Cr ratio on right thalamus was positively related with age of onset ( r = 0. 25, P ＜0.05 ). In negative subtype schizophrenics of non-first-episode, without-medicine, the correlation was negative between the NAA/Cr ratio and the course of disease( r= -0.48, -0.46, P＜0.05 ) ,and was positive between Cho/Cr ratio and the course of disease on right thalamus( r= 0.58,0.56, P＜ 0.01 ). Conlusion Compared with positive subtype schizophrenics,negative subtype schizophrenics have greater impairments on 1 H-MRS on right thalamus. The course of disease has greater effects on 1 H-MRS in negative subtype schizophrenics.
ABSTRACT
Skull recognition is a new method of biometrics recognition. A skull recognition algorithm is presented in this paper by Quadratic rational Bezier curve fitting which accurately describes the feature of skull edge; the experiment results based on skull x-ray image show the correctness of this method.
Subject(s)
Humans , Algorithms , Artifacts , Pattern Recognition, Automated , Methods , Radiographic Image Enhancement , Methods , Radiographic Image Interpretation, Computer-Assisted , Methods , Skull , Diagnostic ImagingABSTRACT
Biometric recognition methods for human identification have received researchers' attention. Seeing that the prominent characteristics of skull biometrics are not affected by facial expression and illumination, we present a new approach compounded of several features. Firstly, comparing the crania included angle; secondly, sampling the edge as the skull feature and analyzing the skull feature in multi-resolution; lastly, calculating the crania cavity area and regularizing the recognition rules. This method supports human identification in cases not only ante mortem but also postmortem.