We observed a remarkable improvement in the performance of COBAS AmpliPrep/COBAS TaqMan version 2.0 Assay over Amplicor Monitor version 1.5 in the quantification of HIV1 RNA viral load. Discrepancies of clinical significance, in the viral load between the two platforms were also recorded. The implications of the inability of the automated Taqman 2.0 to detect 2.4% of samples detectable by the Amplicor need to be considered by programs, clinicians and the manufacturers. Periodic evaluation of platforms to detect new circulating HIV subtypes within each locality is also recommended.

Automated Breast Ultrasound (ABUS) is an image interpretation to detect the breast tumors. Tumor detection has become a challenging task, due to the presence of poor image contrast, speckle noise and irregular tumor shape. The scope of the work is to remove the speckle noise efficiently while preserving important information from the tumor boundaries. Bilateral filter and the Bivariate Shrinkage Function is applied to the automated whole breast ultrasonic image for the removal of speckle noise. A topographic watershed transform is implemented for ABUS image segmentation process where the précised contour of breast tumors is extracted automatically. This segmented lesion extracts various features like GLCM features, Tamura features, MCHOG features and shape features. Binary logistic regression classifier is applied to the selected feature vectors to analyze the tumor and nontumor images.