Bio-Medical Image Processing: Medical Image Analysis for Malaria With Deep Learning

Bio-Medical Image Processing: Medical Image Analysis for Malaria With Deep Learning

Rasmita Lenka (KIIT University (Deemed), India), Koustav Dutta (KIIT University (Deemed), India), Ashimananda Khandual (College of Engineering and Technology, India) and Soumya Ranjan Nayak (Chitkara University, India)
Copyright: © 2020 |Pages: 12
DOI: 10.4018/978-1-7998-0066-8.ch007
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Abstract

The chapter focuses on application of digital image processing and deep learning for analyzing the occurrence of malaria from the medical reports. This approach is helpful in quick identification of the disease from the preliminary tests which are carried out in a person affected by malaria. The combination of deep learning has made the process much advanced as the convolutional neural network is able to gain deeper insights from the medical images of the person. Since traditional methods are not able to detect malaria properly and quickly, by means of convolutional neural networks, the early detection of malaria has been possible, and thus, this process will open a new door in the world of medical science.
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There are many components that make an area susceptible to an infectious disease outbreak. We’ll the primary constituents below

  • Poverty Level: When assessing the risk of infectious disease outbreak, we typically examine how many people in the population or at or below poverty levels. The higher the poverty level, the higher the risk of infectious disease, although some researchers will say the opposite — that malaria causes poverty. Whichever the cause we all can agree there is a correlation between the two.

  • Access to Proper Healthcare: Regions of the world that are below poverty levels most likely do not have access to proper healthcare. Without good healthcare, proper treatment, and if necessary, quarantine, infectious diseases can spread quickly.

  • War and Government: An area of the world that either has a corrupt government or is experiencing civil war will also have higher poverty levels and lower access to proper healthcare. Furthermore, if may be impossible for a corrupt government to provide emergency medical treatment or issue proper quarantines during a massive outbreak.

  • Disease Transmission Vectors: A disease vector is an agent that carries the disease and spreads it to other organisms. Mosquitoes are notorious for carrying malaria.

Once infected, a human can also be a vector and can spread malaria through blood transfusions, organ transplants, sharing needles/syringes, etc.

Furthermore, warmer climates of the world allow mosquitoes to flourish, further spreading disease. Without proper healthcare, these infectious diseases can lead to endemic proportions.

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Main Focus Of The Chapter

Here, in this section, the existing methods of the tests being conducted for detection of Malaria (Fabio, Gonzalez & Romero, 2009) and the problems faced due the existing methods are being discussed.

Key Terms in this Chapter

Normalize: Multiply (a series, function, or item of data) by a factor that makes the norm or some associated quantity such as an integral equal to a desired value (usually 1).

Neural Network: A computer system modeled on the human brain and nervous system.

Convolution: A function derived from two given functions by integration which expresses how the shape of one is modified by the other.

Antigen: A toxin or other foreign substance which induces an immune response in the body, especially the production of antibodies.

Malaria: An intermittent and remittent fever caused by a protozoan parasite which invades the red blood cells and is transmitted by mosquitoes in many tropical and subtropical regions.

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