Analysis of Biomedical Image for Alzheimer's Disease Detection

Analysis of Biomedical Image for Alzheimer's Disease Detection

Rashmi Kumari, Shashank Pushkar
Copyright: © 2020 |Pages: 28
DOI: 10.4018/978-1-7998-0066-8.ch012
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Abstract

Image analysis is giving a huge breakthrough in every field of science and technology. The image is just a collection of pixels and light intensity. The image capturing was done in two ways: (1) by using infrared sensors and (2) by using radiography. The normal images are captured by using the infrared sensors. Radiography uses the various forms of a light family, such as x-ray, gamma rays, etc., to capture the image. The study of neuroimaging is one of the challenging research topics in the field of biomedical image processing. So, from this note, the motivation for this work is to analyze 3D images to detect Alzheimer's disease and compare the statistical results of the whole brain image data with standard doctor's results. The authors also provide a very short implementation for brain slicing and feature extraction using Freesurfer and OpenNeuro dataset.
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Genetic Factor Behind Alzheimer’S Disease

Alzheimer’s disease (AD) is a common form of neurodegenerative disease. Individuals who are impacted by this disease are aware of causes of dementia. The clinical characterization of Alzheimer’s involves progressive loss of memory deficits in thinking, problem-solving and it has an impact on language abilities. Neuropathlogically AD can be characterized as progressive cortical atrophy due to neural loss and characteristic intracellular and extracellular deposits as insoluble tau and amyloid beta proteins vide Cauwenberghe et al. (2015), this is typically the process in which the disease manifests itself. Study of this disease based on genetically classification provides some important insights. Patients can be divided into two groups one is early onset and the other is late onset. For early onset, studies represent that there is a small set of genes that can be responsible for early onset of the disease but early-onset cases are fraction around five to 10 percent of total observed cases of these patients of early onset 2 to 10 percentage first display symptoms their 20s or their 30s. But the late onset of Alzheimer’s tends to manifest itself after the age of 65. Late onset is pretty complex and is multifactorial, which means multiple genes could be involved and contributing to the disease and it has been found there is a pretty strong genetic predisposition. We have seen that about 30 to 48 percent of patients with Alzheimer’s tend to have a first degree relatives that are also affected. So in trying to pinpoint which genetic risk are contributing to the disease, a number of Genome-wide association studies (GWAS) have been conducted GWAS helped in identifying as a community of 20 plus genetic risk loci, but these loci have small odds ratio. Hence none of them are really clear contenders to contribute to the disease. These loci include both common functional variants, and also rare and structural variants in that makeup. These are shown in Figure 1.

Figure 1.

Complex genetic makeup of AD

978-1-7998-0066-8.ch012.f01

Genetics is a very important and interesting factor. Every individual is born with a particular set of genes and the assortment of genes that we have determined the number of things that might happen to us during life. Alzheimer’s disease is no exception and there are different types of genetic effects on people’s risk of developing Alzheimer’s disease. Some of these can be very extreme or strongly predictive. These are associated with rather rare families who are at risk for developing early onset of Alzheimer’s disease in a familial fashion. In this case, multiple people within a family will be affected. The age of onset is usually under the age of 50 and very often in the 30s as well as 40s. So, in these families, the fact is that a mutation in a gene really causes Alzheimer’s disease. There are three genes that were identified in the 1990s that are responsible for early-onset familial Alzheimer’s disease Cauwenberghe et al. (2015) and Brookmeyer et al. (2007).

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