Abstract: Rheumatoid Arthritis (RA) is a chronic inflammatory joint disease characterized by a distinctive pattern of bone and joint destruction. To give an RA diagnosis, hand bone radiographs are taken and analyzed. A hand bone radiograph analysis starts with the bone boundary detection. It is however an extremely exhausting and time consuming task for radiologists. An automatic bone boundary detection in hand radiographs is thus strongly required. Garcia et al. have proposed a method for automatic bone boundary detection in hand radiographs by using an adaptive snake method, but it doesn’t work for those affected by RA. The level set method has advantages over the snake method. It however often leads to either a complete breakdown or a premature termination of the curve evolution process, resulting in unsatisfactory results. For those reasons, we propose a modified level set method for detecting bone boundaries in hand radiographs affected by RA. Texture analysis is also applied for distinguishing the hand bones and other areas. Evaluating the experiments using a particular set of hand bone radiographs, the effectiveness of the proposed method has been proved.

Syaiful Anam, Eiji Uchino, Hideaki Misawa and Noriaki Suetake, “Texture Analysis and Modified Level Set Method for Automatic Detection of Bone Boundaries in Hand Radiographs” International Journal of Advanced Computer Science and Applications(IJACSA), 5(10), 2014. http://dx.doi.org/10.14569/IJACSA.2014.051017

@article{Anam2014,
title = {Texture Analysis and Modified Level Set Method for Automatic Detection of Bone Boundaries in Hand Radiographs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.051017},
url = {http://dx.doi.org/10.14569/IJACSA.2014.051017},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {10},
author = {Syaiful Anam and Eiji Uchino and Hideaki Misawa and Noriaki Suetake}
}