Artificial Intelligence Applications in Classification and Segmentation of Small Uterine Fibroids Using MRI Images Depending on Deep Convolutional Neural Networks - Duraid Manea Bashara,; Fathinul Fikri Ahmed Saad, (American Journal of Biology and Natural Sciences, 2025)
MRI (Magnetic Resonance Imaging) is now frequently used to diagnose uterine fibroids and to determine the treatment approach for minimally invasive surgery and non-invasive focused ultrasound (HIFU) surgery. However, MRI images of some fibroids can be difficult to identify accurately. In this paper, we explain in simple terms the approaches used in the Artificial Intelligence (AI) study of MRI imaging that can analyses, learn, and increase the sensitivity of determining the sizes, locations, number of fibroids, and their abnormalities. The difficulties and limitations of AI application to automatic analysis of MRI fibroid images in our early study are discussed. This paper hopes to arouse the interest of medical professionals to understand how the mechanism of AI can help analyses MRI images and incorporate AI into their daily imaging work.