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MRI High Dimensional Data and Statistical Analysis on Spinal Cord Injury Detection

MRI High Dimensional Data and Statistical Analysis on Spinal Cord Injury Detection

K. Uday Kiran, Ella Kalpana, Prabha Shreeraj Nair, S. K. Hasane Ahammad, K. Saikumar
Copyright: © 2023 |Pages: 14
ISBN13: 9781668469712|ISBN10: 1668469715|EISBN13: 9781668469729
DOI: 10.4018/978-1-6684-6971-2.ch008
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MLA

Uday Kiran, K., et al. "MRI High Dimensional Data and Statistical Analysis on Spinal Cord Injury Detection." Handbook of Research on Advancements in AI and IoT Convergence Technologies, edited by Jingyuan Zhao, et al., IGI Global, 2023, pp. 131-144. https://doi.org/10.4018/978-1-6684-6971-2.ch008

APA

Uday Kiran, K., Kalpana, E., Nair, P. S., Ahammad, S. K., & Saikumar, K. (2023). MRI High Dimensional Data and Statistical Analysis on Spinal Cord Injury Detection. In J. Zhao, V. Kumar, R. Natarajan, & T. Mahesh (Eds.), Handbook of Research on Advancements in AI and IoT Convergence Technologies (pp. 131-144). IGI Global. https://doi.org/10.4018/978-1-6684-6971-2.ch008

Chicago

Uday Kiran, K., et al. "MRI High Dimensional Data and Statistical Analysis on Spinal Cord Injury Detection." In Handbook of Research on Advancements in AI and IoT Convergence Technologies, edited by Jingyuan Zhao, et al., 131-144. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-6971-2.ch008

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Abstract

The MRI spinal cord image-based injury detection is very complex in the current world. In this research, an advanced deep learning-based spinal injury detection algorithm has been proposed. The segmentation was performed with the Otsu technique. The feature extraction and training were performed with shape-based intensity parameters of nothing but standard deviation, variance, mean, and kurtosis. The testing can be possible with ResNet CNN technology. The classification has been performed through 167 layers of architecture. Finally, with confusion matrix accuracy of 98.43%, Recall97.34%, F 1 measure of 95.23%, and throughput of 96.76%.

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