Health information system model for monitoring treatment and surveillance for leprosy patients in indonesia (case study in Pekalongan District, Central Java, Indonesia).

After India and Brazil, Indonesia has the third highest incidence/prevalence of leprosy in the world. Every year thousands of new cases and case with grade-2 disability are reported and, while the recovery rate lingers only 80-90 %. Therefore, more than 10 % of leprosy patients drop out of treatment and can be a source of new infections in the community. Our research was aimed at determining apparent difficulties in the leprosy control program as well as how a health information system (HIS) could assist the Indonesian leprosy control program. We used qualitative method with deep interview and observation of document. One of the difficulties which the Indonesian leprosy control program faces is discontinuity of patient's data due to rotating staff as well as the treatment monitoring and queries patients which should be monitored after treatment has ceased. Technology implementation is feasible through short message service (sms) reminders and web base applications. The leprosy control program urgently needs to implement continuous monitoring and recording of patients because of the particular characteristics of this contagious disease.

EndNote 7.0.

EndNote is a useful software for online literature search and efficient bibliography management. It helps to format the bibliography according to the citation style of each journal. EndNote stores references in a library file, which can be shared with others. It can connect to online resources like PubMed and retrieve search results as per the search criteria. It can also effortlessly integrate with popular word processors like MS Word. The Indian Journal of Dermatology, Venereology and Leprology website has a provision to import references to EndNote.

Measurement of retinal vessel widths from fundus images based on 2-D modeling.

Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.