Comparative Study On Enhancement Of Micro CT Images Using Artificial Intelligence

Micro-computed tomography (CT) imagining is an advanced technology that has been commonly adapted to scan three-dimensional images of small animals and small structures. Micro CT has a wide variety of applications in medical science, medical research, material science, etc. Micro CT provides low-dose scanning to ensure that the scanning material is safe and the radiation explosion is low. Although it is a low-dose scanning method, the quality of the scanned image will be somewhat degraded. In the specialized domain of image processing, we see enormous triumph in the regions of artificial intelligence (AI) and deep learning (DL) as well, with the capacity to deal with even the most difficult operations like reconstruction, enhancement, segmentation, etc. The main aim of this literature survey is to study the existing AI-based approaches like the convolutional neural network (CNN), generative adversarial network (GAN), AutoEncoders, etc for the enhancement of micro CT images and to compare the features of different models. This literature review shows all the potential methodologies for enhancing medical images using AI. This survey allows for comprehension of existing image-enhancing approaches as well as the research needed in the field.