A New Approach for Enhancing the Quality of Medical Computerized Tomography Images

Computerized tomography (CT) images contribute immensely to medical research and diagnosis. However, due to degradative factors such as noise, low contrast, and blurring, CT images tend to be a degraded representation of the actual body or part under investigation. To reduce the risk of imprecise diagnosis associated with poor-quality CT images, this paper presents a new technique designed to enhance the quality of medical CT images. The main objective is to improve the appearance of CT images in order to obtain better visual interpretation and analysis, which is expected to ease the diagnosis process. The proposed technique involves applying a median filter to remove noise from the CT images and then using a Laplacian filter to enhance the edges and the contrast in the images. Also, as CT images suffer from low contrast, a Contrast Limited Adaptive Histogram Equalization transform is also applied to solve this problem. The main strength of this transform is its modest computational requirements, ease of application, and excellent results for most images. According to a subjective assessment by a group of radiologists, the proposed technique resulted in excellent enhancement, including that of the contrast and the edges of medical CT images. From a medical perspective, the proposed technique was able to clarify the arteries, tissues, and lung nodules in the CT images. In addition, blurred nodules in chest CT images were enhanced effectively. Therefore the proposed technique can help radiologists to better detect lung nodules and can also assist in diagnosing the presence of tumours and in the detection of abnormal growths.

@article{Al-Frejat2016,
  title     = {A New Approach for Enhancing the Quality of Medical Computerized Tomography Images},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {5},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Mutaz Al-Frejat and Mohammad HjoujBtoush},
  doi       = {10.14569/IJACSA.2016.070564},
  url       = {https://doi.org/10.14569/IJACSA.2016.070564}
}