Development of Intelligent Medical Image Restoration System

Computed tomography (CT) is an imaging procedure that uses special X-ray equipment to create detailed scans of areas inside the human body. However, in spite of the tremendous contributions of CT to modern health care, some attention must also be given to the health risk associated with the radiation received during a CT exam. An important current issue in the field of CT is to reduce radiation exposure by more effective dose control while maintaining standard image quality. However, low-dose CT images suffer from severe noise artifacts and reduced feature details which impeding diagnosis capability. So, improve the diagnostic quality of CT images has become an attractive research topic and many methods have been proposed to remove the significant noise and streak artifacts in the reconstructed images. In this book, an image-space denoising filter in conjunction with a database of priors is introduced for the restoration of low-dose CT images.

Autorentext

F. Harby has a PhD in Mathematics (Computer Science) earned at Suez Canal University (2017). Lecturer at Workers University, Egypt, she is interested in medical imaging field, image processing, artificial neural network and machine learning. She has a good experience in learning, teaching and using research tools in the field of Computer Science.