Object Contour in Low Quality Medical Images in Curvelet Domain

Abstract: The diagnosis and treatment are very important for extending the life of patients. The small abnormalities may also be manifestations of the diseases. One of the abnormalities is the contour of each object in medical images. Therefore, the contour is very important and special to low quality medical images. In this paper, we propose a new method to detect the object contour of low quality medical images based on the self affine snake, one of the types of active contour models. The method includes two periods. Firstly, we use augmented lagrangian method to remove noise and detect edges in low quality medical images in curvelet domain. Finally, the active contour model is improved to show the contour of objects. After comparing the appearance of the contour and the time processing with other algorithms, we confirm that the proposed method is better.

Vo Thi Hong Tuyet and Nguyen Thanh Binh. “Object Contour in Low Quality Medical Images in Curvelet Domain”. International Journal of Advanced Computer Science and Applications (IJACSA) 9.4 (2018). http://dx.doi.org/10.14569/IJACSA.2018.090409

@article{Tuyet2018,
title = {Object Contour in Low Quality Medical Images in Curvelet Domain},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090409},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090409},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {4},
author = {Vo Thi Hong Tuyet and Nguyen Thanh Binh}
}