Harvendra Singh Bhadauria

TL;DR: This work proposes a novel technique to differentiate ALL (acute lymphoblastic leukemia) lymphoblast cells from healthy lymphocytes by first separate leukocytes from the other blood cells and then lymphocytes are extracted.

TL;DR: An attempt has been made to design a CAC (computer aided classification system) for diagnosis of myeloid and lymphoid cells and their FAB (French, American, and British) characterization and improves the AML and ALL diagnostic accuracy by analyzing color, morphological and textural features from the blood image using image processing.

TL;DR: A noise reduction method for both computed tomography (CT) and magnetic resonance imaging (MRI) which fuses the images and extracts edge information from the noise residual of TV method by processing it through curvelet transform.

TL;DR: This work addresses the problem of segmenting a microscopic blood image into different regions, and then further analyzes those regions for localization of the immature lymphoblast cell, and investigates the use of different geometrical, chromatic and statistical textures features for nucleus as well as cytoplasm and pattern recognition techniques for sub typing immature acute lymphoblasts as per FAB (French– American – British) classification.

TL;DR: This article aims at classification, working and comparative analysis of these models proposed by researchers to deploy SNs in large-scale open regions.