Chinese version of the Perth Alexithymia Questionnaire:psychometric properties and clinical applications

Background The alexithymia trait is of high clinical interest.The Perth Alexithymia Questionnaire(PAQ)was recently developed to enable detailed facet-level and valence-specific assessments of alexithymia.Aims In this paper,we introduce the first Chinese version of the PAQ and examine its psychometric properties and clinical applications.Methods In Study 1,the PAQ was administered to 990 Chinese participants.We examined its factor structure,internal consistency,test-retest reliability,as well as convergent,concurrent and discriminant validity.In Study 2,four groups,including a major depressive disorder(MDD)group(n=50),a matched healthy control group for MDD(n=50),a subclinical depression group(n=50)and a matched healthy control group for subclinical depression(n=50),were recruited.Group comparisons were conducted to assess the clinical relevance of the PAQ.Results In Study 1,the intended five-factor structure of the PAQ was found to fit the data well.The PAQ showed good internal consistency and test-retest reliability,as well as good convergent,concurrent and discriminant validity.In Study 2,the PAQ was able to successfully distinguish the MDD group and the subclinical depression group from their matched healthy controls.Conclusions The Chinese version of the PAQ is a valid and reliable instrument for comprehensively assessing alexithymia in the general population and adults with clinical/subclinical depression.

Medical Image Segmentation Based on Wavelet Analysis and Gradient Vector Flow

Medical image segmentation is one of the key technologies in computer aided diagnosis. Due to the complexity and diversity of medical images, the wavelet multi-scale analysis is introduced into GVF (gradient vector flow) snake model. The modulus values of each scale and phase angle values are calculated using wavelet transform, and the local maximum points of modulus values, which are the contours of the object edges, are obtained along phase angle direction at each scale. Then, location of the edges of the object and segmentation is implemented by GVF snake model. The experiments on some medical images show that the improved algorithm has small amount of computation, fast convergence and good robustness to noise.