Automatic Detection of Sinusitis and Analyzing the Severity with Preventive Measures using GUI MATLAB Tools
P Sasi Kiran1, M. Sailaja2

1P Sasi Kiran, Department of Electronics & Communication Engineering, Vignan’s Institute of Information Technology, Visakhapatnam (A.P), India.
2M Sailaja, Department of Electronics & Communication Engineering, Vignan’s Institute of Information Technology, Visakhapatnam (A.P), India.

Manuscript received on 18 October 2012 | Revised Manuscript received on 25 October 2012 | Manuscript published on 30 October 2012 | PP: 20-24 | Volume-1 Issue-4, October 2012 | Retrieval Number: D0319091412/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Sinusitis is treated with medications or surgery for severe cases. Imaging techniques are popular in detecting sinusitis as they are less intrusive. Current imaging techniques used to detect sinusitis are the X-ray, CT scan and MRI scan. Images taken with these imaging techniques have to be interpreted by doctors manually and this gives room for inconsistency or in some cases, inaccuracy. Image segmentation is important as the results of segmentation are used for diagnosis and surgical planning. At present, manual segmentation and semi-automatic segmentations are used. Another approach is the Discrete Curvelet Transform which is a new image representation. This approach is based on the idea of representing a curve as superposition of functions of various length and width obeying the lam: width ~ length2 , this called the Curvelet Scaling Law. Due to the high ability of the Curvelet transform in representing the edges, modification of Curvelet transform coefficients to enhance the sinusitis image edges better prepares the image for the segmentation part. The software used for simulations is Image processing tools in MATLAB using GUI. Simulations are performed on images of healthy sinuses and sinuses with sinusitis.
Keywords: Curvelet Transforms, Sinusitis, GUI.

Scope of the Article: Image analysis and Processing