Enhancing X-Ray Image Quality For Improved Medical Diagnosis: A Novel Filtering Algorithm

This paper presents a novel image processing algorithm for enhancing the quality of X-ray images, with the aim of improving the accuracy and efficiency of medical diagnosis. The algorithm combines two types of filters: the Cream filter, based on the work of Lefranc-Bustamante, and the Bosso filter, which uses a Gaussian function. These filters model the degradation in the quality of X-ray images due to the effects of radiation scattering and attenuation. The proposed algorithm was evaluated on three types of images: knee, breast, and wrist, and the results show a significant improvement in contrast and sharpness, particularly in knee and wrist images. The behavior of entropy and contrast as a function of the filtering parameter d was also analyzed, and the implications of these findings are discussed. The paper concludes by suggesting further explorations of the algorithm in different Xray imaging techniques and the potential impact of these improvements on the accuracy of medical diagnosis.