Search

The process of aligning one image, in the coordinate system of another is called registration. Image registration is vital in the medical domain and is used for diagnosis, therapy planning, and treatment of diseases. Due to its huge applicability and importance, medical image registration has emerged to be a separate domain of research. Beginning from the invasive landmark based registration, innumerable algorithms have been proposed to register two images of the human physiology. However, a breakthrough in the literature occurred when an information theory based measure, mutual information was used to register two images. Since then a large number of new algorithms have developed, which use mutual information for fully automatic registration of medical images. This paper is a survey of these algorithms. Beginning from its development, it discusses about some of the major works done on mutual information based image registration. Some comparative studies with other algorithms have also been discussed. The paper ends with a discussion of the developments in medical image registration algorithms post mutual information, which primarily include deep neural network (DNN) based algorithms. [ABSTRACT FROM AUTHOR]

A language family is a group of languages which have descended from a common mother language. Since the ancestor is common, these languages are expected to be similar in some respect and manifest the similarity in scientific experiments. In language identification, language-specific features are extracted from speech and a model is created which represents the language. This work extends the language identification framework to capture features common to language families and create models which can efficiently represent the language families. Mel frequency cepstral coefficient (MFCC) and speech signal-based frequency cepstral coefficient (SFCC) are used as primary feature extraction tools. A combination of these along with shifted delta coefficient (SDC) gives the final set of features. The work uses Gaussian mixture model (GMM) and support vector machines (SVM) as modelling tools. Different combinations of these feature extraction and modelling techniques are used to get four different systems: MFCC + SDC + GMM, SFCC + SDC + GMM, MFCC + SDC + SVM and SFCC + SDC + SVM. Experiments with these systems show that the language families can be identified with reasonable accuracy. Further, the work tests the influence of one language family on the other and finds that in most cases, the languages which are spoken in areas lying on the boundary of two families are more influenced by the other family. A deviation from it can relate to geopolitical isolation of two neighbouring regions and thus can give new insights or corroborate investigations of historians. [ABSTRACT FROM AUTHOR]

Washington, DC, is a metropolitan city with a severe HIV epidemic and faces challenges in retaining people living with HIV (PLWH) in quality care. This study assessed site migration in seeking care services and its correlates among PLWH in DC. PLWH diagnosed before 2008 and living through the end of 2010 were analyzed. Six scenarios of site migration were examined as patients visited =2, =3, and =4 different providers for their CD4 cell count and/or viral load (VL) tests in the past 3 years from 2008 to 2010 and 2 years from 2009 to 2010, respectively. Of 6480 patients analyzed from 2008 to 2010, 18.4% had CD4 < 200 cells/mm3, 30.5% had VL > 400 copies/mL, and 76.6% were retained in same care sites; 23.4%, 5.0%, and 0.9% visited =2, =3, and =4 sites in the past 3 years from 2008 to 2010, respectively. Of 5954 patients analyzed from 2009 to 2010, 16.8% had CD4 < 200 cells/mm3, 29.4% had VL > 400 copies/mL, and 81.9% were retained in same care sites; 18.1%, 3.1%, and 0.6% visited =2, =3, and =4 sites in the past 2 years from 2009 to 2010, respectively. Multivariable logistic regression analyses revealed that migration across six scenarios are consistently associated with CD4 < 200 cells/mm3and VL > 400 copies/mL. Site migration was common and associated with lower CD4 and higher VL among PLWH in DC. Frequent migration might be a factor in achieving optimal health outcomes for a subset of patients. Site migration might potentially limit effective delivery of high quality care and treatment services. The preliminary findings underscore the need for further research to assess the predictors of migration and its impact on stage of care. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article ‘'Identification of the major language families of India and evaluation of their mutual influence'' by D.Sengupta and G. Saha in the December 25, 2016 issue.