Detection of pulpal calcifications on bite-wing radiographs using deep learning

Performance Evaluation of Different Deep Learning Models for Classifying Ischemic, Hemorrhagic, and Normal Computed Tomography Images: Transfer Learning Approaches

“…In radiological image analysis, difficulties such as the necessity of intervention in a short time, problems in accessing specialists who need to interpret images, limitations of facilities in hospitals in small regions, and shortages in the number of radiologists can be encountered. Considering all the disadvantages mentioned, to overcome these shortcomings, the number of studies on image processing and artificial intelligence-based radiological image analysis has been increasing recently and continues to be a hot topic in the literature [4,5]. Deep learning models have recently been used frequently in the literature for the classification, segmentation, and object detection of medical images [5][6][7].…”

“…Considering all the disadvantages mentioned, to overcome these shortcomings, the number of studies on image processing and artificial intelligence-based radiological image analysis has been increasing recently and continues to be a hot topic in the literature [4,5]. Deep learning models have recently been used frequently in the literature for the classification, segmentation, and object detection of medical images [5][6][7]. In medical studies, where classical machine-learning methods were used for a period, deep-learning models began to be used over time.…”