Identification of Bone Fracture using Image Processing

Author:

S Upadhyay Rocky1,Tanwar Prakash Singh2

Affiliation:

1. Research Scholar, Computer Science and Engineering, Madhav University, Sirohi, Rajasthan, India

2. Head, Department of CSE & CSA, Madhav University, Sirohi, Rajasthan, India

Abstract

In current period, broken bones is a typical problem in normal human happens because of high weight is applied on bone or basic mishap and furthermore because of cancer of bone and osteoporosis. So, the exact determination of bone crack is significant viewpoints in therapeutic arena. From this research X-beam/CT pictures are utilized for object crack analysis. The picture handling systems are helpful for some applications, for example, science, security, satellite symbolism, individual photograph, medicine, etc. The techniques of picture handling, for example, picture upgrade, picture division and highlight extraction are utilized for crack recognition system. This paper utilizes canny edge location strategy for segmentation. Canny strategy produces ideal data from the bone picture. The principle point of this examination is to recognize human lower leg bone crack from X-Ray images. The tests we lead show that the proposed framework is precise and ef?cient.

Publisher

Technoscience Academy

Subject

General Medicine

Reference11 articles.

1. Vijaykumar, V., Vanathi, P., Kanagasabapathy, P. (2010). Fast and efficient algorithm to remove gaussian noise in digital images. IAENG International Journal of Computer Science, 37(1).

2. Al-Khaffaf, H., Talib, A. Z., Salam, R. A. (2008). Removing salt-and-pepper noise from binary images of engineering drawings. In: Pattern Recognition. ICPR. 19th International Conference on, p. 1–4. IEEE.

3. S.K.Mahndran, S.Santhosh BaBoo, An Enhanced Tibia Fracture Detection Tool Using Image Processing and Classification Fusion Techniques in X-Ray Images, Sankara College of Science and Commerce, Coimbatote, Tamil Nadu, India, Online ISSN: 0975-4172 &Print ISSN: 0975-4350, Volume 11 Issue 14 Version 1.0 August 2011

4. S.K.Mahndran, S.Santhosh BaBoo, An Ensemble Systems for Automatic Fracture Detection, IACIT International Journal of Engineering and Technology, Vol.4, No. 1, Fenruary 2012.

5. Rashmi, Mukesh Kumar, and Rohini Saxena, Algorithm And Technique On Various Edge Detection: A Survey, Department of Electronics and Communication Engineering, SHIATS- Allahabad, UP.-India, Vol. 4, No. 3, June 2013.

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