THE USE OF ARTIFICIAL INTELLIGENCE ON COLPOSCOPY IMAGES AND SEGMENTAL VOLUMES, CONSTRUCTED FROM MRI AND CT IMAGES, IN THE DIAGNOSIS AND STAGING OF PRECANCERS, CERVICAL CANCERS AND THYROID CANCERS - Hlescu Cristian Stefan; Tudor Florin Ursuleanu; Roxana Grigorovici; Andreea Roxana Luca; Ramona Elena Teiu; Maria Paula Comanescu; Alina Ionela Calin; Alexandru Grigorovici (Romanian Journal of Oral Rehabilitation)
Aim of the study For the accurate diagnosis and staging of precancers and cervical and thyroid cancer, we aim to create a diagnostic method optimized by artificial intelligence (AI) algorithms and validated by the notable positive results of a randomized, controlled, 17-month trial.. Materials and methods The optimization of the method will involve the development and training of artificial intelligence models using convolutive neural networks (CNN) to identify precancers and cancers in colposcopic images. We will use topologies that have demonstrated strong performance in similar image recognition projects, such as VGG16, Inception, MobilNet, ROI, U-Net, and KiU-Net. Additionally, the research includes a comparative study of various algorithms and tools employed in segmental volumetric constructions to generate 3D images from MRI/CT data.