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Neuron Loss Quantification Using Histogram Analysis

Undergraduate #378
Discipline: Technology and Engineering
Subcategory: Biomedical Engineering

Aliyah Mcilwain - Lincoln University
Co-Author(s): Doneisha Steele and Ezra Connell, Lincoln University, PA



Neurons are the core component of the brain. They are electrically excitable cells that transmit information by electrochemical signaling. A neuron can connect to up to 10,000 other neurons and pass signals to each other through synaptic connections. While neurons are the main form of communication in the brain, they are non-regenerative cells. Being non-regenerative in nature means that neurons will be permanently gone after loss. A loss of neurons relates to slower memory processing and overall deterioration of the mind; leading to degenerative diseases like Dementia, Alzheimer’s, or Parkinson’s disease. Comparing multiple images of the same neuron, the progression of neuron degeneration can be traced using digital image processing algorithms that would be helpful to medical examiners. A digital image is defined as a two dimensional matrix or a function f(x,y), where x and y are spatial coordinates, and the value of f(x,y) is defined as the intensity of the image pixels or matrix entries, where x, y, and the amplitude values of f are all finite, discrete quantities. An image histogram reflects a graphical representation of the pixel gray level intensity distribution in a digital image. The horizontal axis of the histogram represents the pixel gray level intensity variations, and the vertical axis represents the number of pixels having that particular pixel gray level intensity. The histogram analysis of a specific image gives the entire grey level intensity distribution. In order to track the degeneration of a neuron, healthy neuron and degenerated neuron images are compared. Therefore, the healthy and degenerated neuron images differ significantly in their grey level intensity distribution i.e. in pixel intensity or amplitude. In this case a higher intensity (light pixels) found predominantly in a healthy neuron image compared to a degenerated neuron image, reflect higher presence of neurites (dendrites and axons) and cell bodies while morphological changes in the neurites (dendrites and axons) and cell bodies of the degenerated neuron image show predominantly darker tones. We are able to identify the rate and location of degeneration of neurons using Matlab software’s histogram functions on a pair of analyzed images.
References: R. C. Gonzalez, R. E. Woods, S. L. Eddins ‘Digital Image Processing Using MATLAB’, ISBN-13: 978-0982085400
Rafael C. Gonzalez, Richard E. Woods ‘Digital Image Processing’, ISBN-13: 978-0131687288
‘What is Neurodegenerative Disease’’ EU Joint Programme – Neurodegenerative Disease Research (JPND). JPND Research, n.d. Web. 12 Oct. 2016.

Funder Acknowledgement(s): I would like to thank Dr. Baskerville for her expertise in the area of Neuroscience and for providing us with microscopy images of cortical neurons. Funding was provided by NSF/HBCU-UP to Dr. Zeljkovic.

Faculty Advisor: Vesna Zeljkovic, vzeljkovic@lincoln.edu

Role: I developed mathematical and simulation models in MATLAB using digital image processing techniques.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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