Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jun 29:2022:9063880.
doi: 10.1155/2022/9063880. eCollection 2022.

Classification of Transgenic Mice by Retinal Imaging Using SVMS

Farrukh Sayeed  1 , K Rafeeq Ahmed  2 , M S Vinmathi  3 , A Indira Priyadarsini  4 , Charles Babu Gundupalli  5 , Vikas Tripathi  6 , Wesam Shishah  7 , Venkatesa Prabhu Sundramurthy  8
Affiliations

Classification of Transgenic Mice by Retinal Imaging Using SVMS

Farrukh Sayeed et al. Comput Intell Neurosci. .

Abstract

Alzheimer's disease is the neuro disorder which characterized by means of Amyloid- β (A β) in brain. However, accurate detection of this disease is a challenging task since the pathological issues of brain are complex in identification. In this paper, the changes associated with the retinal imaging for Alzheimer's disease are classified into two classes such as wild-type (WT) and transgenic mice model (TMM). For testing, optical coherence tomography (OCT) images are used to classify into two groups. The classification is implemented by support vector machines with the optimum kernel selection using a genetic algorithm. Among several kernel functions of SVM, the radial basis kernel function provides the better classification result. In order to deal with an effective classification using SVM, texture features of retinal images are extracted and selected. The overall accuracy reached 92% and 91% of precision for the classification of transgenic mice.

PubMed Disclaimer

Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Figure 1
Figure 1
Typical flow for transgenic mice.
Figure 2
Figure 2
Proposed work.
Figure 3
Figure 3
SVM for classification of transgenic mice.
Figure 4
Figure 4
(a) and (b) retinal images, and (c), (d) OCT images.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Chibhabha F., Yang Y., Ying K., et al. Non-invasive optical imaging of retinal Aβ plaques using curcumin loaded polymeric micelles in APPswe/PS1ΔE9 transgenic mice for the diagnosis of Alzheimer’s disease. Journal of Materials Chemistry.B . 2020;8 - PubMed
    1. Kumar S., Berriochoa Z., Ambati B. K., Fu Y. Angiographic features of transgenic mice with increased expression of human serine protease HTRA1 in retinal pigment epithelium. Investigative Opthalmology & Visual Science . 2014;55(6):3842–3850. doi: 10.1167/iovs.13-13111. - DOI - PMC - PubMed
    1. Tian J., Smith G., Guo H., et al. Modular machine learning for Alzheimer’s disease classification from retinal vasculature. Scientific Reports . 2021;11(1):p. 238. doi: 10.1038/s41598-020-80312-2. - DOI - PMC - PubMed
    1. Fosnacht A. M. From brain disease to brain health: primary prevention of Alzheimer’s disease and related disorders in a health system using an electronic medical record-based approach. J. Prev. Alzheimer’s Dis. . 2017;4(3):157–164. - PMC - PubMed
    1. Doustar J., Rentsendorj A., Torbati T., et al. Parallels between retinal and brain pathology and response to immunotherapy in old, late‐stage Alzheimer’s disease mouse models. Aging Cell . 2020;19 doi: 10.1111/acel.13246. - DOI - PMC - PubMed