Parasite Detection Model for Neglected Tropical Disease Diagnosis

Kato-katz is the most commonly used microscopy-based technique in the diagnosis of Neglected Tropical Diseases (NTDs). This paper describes the preliminary studies that are involved in the automated detection of parasitic eggs in a given Kato-katz image. The studies involve application of pattern recognition techniques based on template matching to detect the presence of parasites in the images of kato-katz slides. The results from this study indicate that using a combination of image segmentation and pattern recognition algorithms generates better results as they deal with the complex nature of the images, such as their spurious intensity patterns and shapes. Clinical Relevance— This paper describes interdisciplinary work that applies image processing algorithms to kato-katz images to solve clinical parasitology problems

A Reflective Analysis of Image Processing Operations on Kato-Katz Images for the Pathological Diagnosis of Neglected Tropical Diseases

This paper gives an insight into the interdisciplinary work that has been carried out to diagnose some of the neglected tropical diseases, in particular micro-parasitic diseases, using image processing operations. The infections from micro-parasites are collectively called Helminthiasis. The Kato-Katz method is a slide scanning technique commonly used for the qualitative and semi-quantitative diagnosis of helminthiasis. This paper explains the image analysis and processing of Kato-katz images to extract meaningful information and convert the qualitative features of the images to quantitative data and thereby effectively diagnose the disease. This is the preliminary stage of a pioneering work done in the field of neglected tropical disease diagnosis and would be beneficial for thousands of people including children in the endemic region

A New Method to Calculate the Spin-Glass Order Parameter of the Two-Dimensional +/-J Ising Model

A new method to numerically calculate the $n$th moment of the spin overlap of the two-dimensional $\pm J$ Ising model is developed using the identity derived by one of the authors (HK) several years ago. By using the method, the $n$th moment of the spin overlap can be calculated as a simple average of the $n$th moment of the total spins with a modified bond probability distribution. The values of the Binder parameter etc have been extensively calculated with the linear size, $L$, up to L=23. The accuracy of the calculations in the present method is similar to that in the conventional transfer matrix method with about $10^{5}$ bond samples. The simple scaling plots of the Binder parameter and the spin-glass susceptibility indicate the existence of a finite-temperature spin-glass phase transition. We find, however, that the estimation of $T_{\rm c}$ is strongly affected by the corrections to scaling within the present data ($L\leq 23$). Thus, there still remains the possibility that $T_{\rm c}=0$, contrary to the recent results which suggest the existence of a finite-temperature spin-glass phase transition.Comment: 10 pages,8 figures: final version to appear in J. Phys.

Image Analysis and Feature Extraction of Kato-Katz Images for Neglected Tropical Diseases Diagnosis

This paper provides an insight into a pioneering interdisciplinary research, amalgamating engineering principles and clinical diagnostic procedures. The research is underway to design and develop an automated parasite diagnostic tool, using machine learning based image processing operations. The preliminary findings of the work in which feature extraction algorithms are applied on clinical images as a base to a neural network model for diagnosis is described in this paper. Maximally Stable Extremal Regions (MSER) was used as a primary feature extractor in the detection of the parasitic eggs. Statistical information regarding the eggs was then collected and compared with background regions in the development of a search algorithm. Using the collected data, a range of values was obtained that could separate the eggs from the background of the images. All the images used are from Kato-katz slides