Despite recent advances, radiographic image segmentation remains a challenging task. This is especially true if the acquired images are degraded by artifact or distracting underlying pathology, conditions under which many state-of-the-art algorithms will fail but which are common in clinical practice. We hypothesize that a deep learning algorithm can be trained for accurate segmentation even in...

Glioblastoma, the most common primary malignant brain tumor in adults, is highly aggressive and associated with a poor prognosis. Bevacizumab, a monoclonal antibody against the vascular endothelial growth factor receptor, has increasingly been used in the treatment of recurrent glioblastoma. It has achieved excellent rates of radiographic response, but most patients will progress after only a f...

introduction in radiography, dose and image quality are dependent on radiographic parameters. the problem is caused from incorrect use of radiography equipment and from the radiation exposure to patients much more than required. therefore, the aim of this study was to implement a quality-control program to detect changes in exposure parameters, which may affect diagnosis or patient radiation do...

Fractal image compression successfully uses selfsimilarity within an image to achieve compression. By adapting fractal image compression techniques to image enhancement, an innovative new fractal technique for visual enhancement of JPEG compressed images is created. After detecting the self-similarity characteristics of a degraded JPEG image, details spoiled by quantization are enhanced using a...

162 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract— The objective of the image enhancement is to remove the noise. Real color images are images with noise. In traditional image enhancement algorithms color images are firstly converted to gray images. These algorithms enhanced noise while they enhanced image. In this paper wavelet transform is used for...