Medical image segmentation is a frequent processing step. Medical images are suffering from unrelated article and strong speckle noise. In this paper, we propose an approach to remove special markings such as arrow symbols and printed text along with medical image segmentation using range filter. The special markings are extracted using Sobel edge detection technique and then the intensity values of the detected markings are substituted by the intensity values of their corresponding neighborhood pixels. Next, three different image enhancement techniques are utilized to remove strong speckle noise as well enhance the weak boundaries of medical images. Finally range filter is applied to segment the texture content of different modalities of medical image. Experiment is conducted on ImageCLEF2010 database. Results show the efficacy of our proposed approach which lead to have precise content based medical image classification and retrieval systems.

The radiographic image has low contrast and high noise. In order to improve the image for observation and accurate analysis, various digital image processing techniques can be applied. In this research we propose Two Dimensional Left Median Filter method for de-noising radiographic images of welding. We have used the measures Peak Signal-to-Noise Ratio and the Mean Absolute Error for comparison. The accuracy of results obtained through our method is better than the Median and Mean Filter methods.