Region of Interest Based Contrast Enhancement Techniques for CT Images
Anureet Kaur, Akshay Girdhar, Navdeep Kanwal · 2016
Medical imaging refers to an approach through which radiographers diagnose the human body using X-rays, CT, ultrasound, and magnetic resonance techniques. It is widely used safe imaging system in medical field that assists in extracting and visualizing the fine details from the image. In order to extract the details from an image, it should be of high quality, but presence of noise in images makes the image unclear and due to this the image enhancement is referred to as the most significant matter of concern in image processing. Every time when the patient is diagnosed, who is suffering from one or the other kind of disease, using techniques of medical imaging, a tumour is located in their body. This tumour can be called as the affected area in the patient's body. To locate this region of interest, various techniques like Otsu method are already available. The intensity difference between the tumour and the other body parts is either low or high but the major problem in detecting the tumour arises when the intensity difference between the tumour and the other organs is very low. Therefore, in order to extract the region, there is a need to enhance the contrast of affected region, so as to distinguish them from other parts. Region of interest based contrast enhancement is a technique to generate and extract the region based on the image contrast of the image. The primary objective of the work is to design a novel algorithm for extracting the affected region. A technique based on level set evolution is described for extracting the region. The proposed technique provides better image quality and contrast to noise ratio. The main focus in the proposed work is on contrast enhancement of CT images based on un-sharp mask filter as a necessary pre-processing. The results thus obtained have been compared with the existing state-of-the-art techniques and the outcomes show that the results are very promising.