Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images.

Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.

Column chromatographic separation of lead(II) using poly [dibenzo-18-crown-6] in L-ascorbic acid.

A column chromatographic separation method has been developed for separation of Lead(II) using poly[dibenzo-18-crown-6]. The separation was carried out in L-ascorbic acid medium. The adsorption of Lead(II) was quantitative from 1 x 10(-2) M to 1 x 10(-7) M L-ascorbic acid. The capacity of poly [dibenzo-18-crown-6] for Lead (II) was found to be 0.530 +/- 0.01 mmol/g of crown polymer. Lead(II) was separated from commonly associated metal ions such as Mg(II), Co(II), Ni(II), Cd(II), Mn(II) Th(IV) and U(VI) and other associated metal ions in binary as well as in multicomponent mixtures. The sorption of Lead was carried out in presence of various ions to ascertain the tolerance limits of individual. The method was extended for the determination of Lead in real samples. The method is simple, rapid and selective having good reproducibility (approximately +/- 2%).