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In this paper, a Spinal unit otherwise known as vertebral column consists of 24 separate bony vertebrae together with 5 fused vertebrae, it is the unique interaction between the solid and fluid components that provide the disc the strength and flexibility required to bear loading of the lumbar spine. In this work Magnitude and Edge Length based Canny Edge Detection Algorithm has been proposed to pre processing of boundary detection of the CT scan Spine disc image. To find the correct boundary in noisy image of spine disc is still a difficult one. The proposed Canny Edge Detection algorithm has been used to detect the boundaries of spine disc image from the noisy image. The performance of proposed technique has been verified and validated with the standard medical values. The results show that the proposed technique performs well and produced very near to the optimal solution. This method is robust for all kinds of noisy images.

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The Finite Element Method [FEM] used to replicate the products and systems. In this method, the abnormality estimation of the spine has developed and presented in this paper. Spine injury found on vertebrae L1–L5 and its corresponding inter-vertebral disk. Different types of filters used to eliminate obtained noise, starting the MRI image at different levels. The noiseless image was segmented using differing Edge Detection Algorithm (EDA) such as Canny Edge Detection Algorithm (CEDA), Prewitt, Sobel, and Robert from the applied segmentation algorithm the best EDA identified and the 3D model for lumbar spine was created. After the segmentation algorithm, the FEA method utilized for examining images of the 3D human lumbar spine on different loads. The experiment conducted with the stress–strain relationship and Modal Analysis on Natural Frequency (NF) calculated. The entire analysis accomplished by real-time simulation software called ANSYS.