Bone Thickness Computation at Low Resolution IN-VIVO CT Images and Classification through ANN

Jayachitra*, M. Usha**
* PG Scholar, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur.
** Assistant Professor, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur.
Periodicity:January - March'2015
DOI : https://doi.org/10.26634/jip.2.1.3263

Abstract

Osteoporosis is a bone disease affecting the bone structure and strength and raising the risk of fractures. Osteoporosis is a bone condition that makes bones thinner and more fragile because of reduced bone density. Osteoporosis may be diagnosed directly through the use of a bone scan that measures bone mineral density (BMD). The micro-architectural quality of Trabecular bone is an important factor of bone quality for evaluating fracture risks under clinical conditions. A new algorithm is implemented for computing TB thickness at a low resolution which is achievable in IN-VIVO images. Here the authors have proposed intercept based algorithm to compute its thickness, and robustness to bone strength. Through this algorithm, the true axis of an object orthogonally intersects a minimum intercept line. By calculating centroids of an image, the thickness is calculated. Detected Image can be classified through artificial neural network classifier.

Keywords

Intercept Based Algorithm, Computed Tomography (CT), Trabecular Bone (TB) Thickness.

How to Cite this Article?

Jayachitra, S., and Usha, M. (2015). Bone Thickness Computation at Low Resolution IN-VIVO CT Images and Classification through ANN. i-manager’s Journal on Image Processing, 2(1), 14-18. https://doi.org/10.26634/jip.2.1.3263

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