Sickle Cell Disease - A Comprehensive Study and Usage of Technology for Diagnosis

Abstract

Sickle cell is haematological disorder (haematology is a study of blood in health and diseases) which may lead to an organ damage, heart strokes and serious complications. It may also reduce human life span. Most of the sickle cells are observed in new born babies. At the start of sickle cells in human people though it’s a kind of feature in tribal people but it has spread over the world. Sickle cell Symptoms are observed in human beings as episodes of pains (crisis), Vision problems, swelling of hands and Feet. Sickle Cell Disease (SCD) can harm patient’s spleen (slightly pain at left Ribs). If one organ is affected in human body, then slowly it affects the entire body by spreading into Brain, Lungs, Heart, Liver, Kidneys, Joints, Eyes, Penis, Skin or Bone. This paper is aimed at presenting the complete details of the SCD with its properties, symptoms, signs, treatment for this disease. This is also a comprehensive study and characteristics of this disease with other similar diseases. The technological implications and usage in the field of SCD for better accuracy of identification of the disease is presented.

Machine Learning Techniques for Automatic Detection of Sickle Cell Anemia using Adaptive Thresholding and Contour-based Segmentation Method

“…This paper also highlights about the technological usage including feature extraction, detection using neural networks (NNs), and SVM for the identification of the disease. [1] Researchers have investigated several segmentation methods for medical image analysis over the years. Among these methods, four categories of segmentation methods are mostly used.…”