Emerging artificial intelligence applications in liver magnetic resonance imaging

Abstract

Chronic liver diseases (CLDs) are becoming increasingly more prevalent in modern society. The use of imaging techniques for early detection, such as magnetic resonance imaging (MRI), is crucial in reducing the impact of these diseases on healthcare systems. Artificial intelligence (AI) algorithms have been shown over the past decade to excel at image-based analysis tasks such as detection and segmentation. When applied to liver MRI, they have the potential to improve clinical decision making, and increase throughput by automating analyses. With Liver diseases becoming more prevalent in society, the need to implement these techniques to utilize liver MRI to its full potential, is paramount. In this review, we report on the current methods and applications of AI methods in liver MRI, with a focus on machine learning and deep learning methods. We assess four main themes of segmentation, classification, image synthesis and artefact detection, and their respective potential in liver MRI and the wider clinic. We provide a brief explanation of some of the algorithms used and explore the current challenges affecting the field. Though there are many hurdles to overcome in implementing AI methods in the clinic, we conclude that AI methods have the potential to positively aid healthcare professionals for years to come.

MRI in liver cirrhosis

“…Furthermore, technical developments to shorten scanning times and combine protocols into single scanning sessions can also improve patient care. Although not discussed in this manuscript, artificial intelligence and its application in MRI images 162 can also magnify the potential of these techniques and decrease the workload of radiologists, something that can help with wider adoption.…”

Mapping the Landscape of Artificial Intelligence Research: A Bibliometric Approach

“…AI-powered health technologies are becoming increasingly prevalent in clinical settings worldwide, with the potential to transform the health system and improve patient care [9]. In liver magnetic resonance imaging, AI algorithms have shown promise in tasks such as detection, segmentation, image synthesis, and artifact detection [10]. In the field of education, AI has been applied to mathematics education, where it has been used for diagnosing individual students' learning problems and providing personalized support [11].…”

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

“…The use of AI techniques in various oncological imaging [ 20 ] for primary malignancies, including breast [ 21 , 22 , 23 ], renal [ 24 , 25 ], brain [ 26 , 27 , 28 , 29 ] and liver cancers [ 30 , 31 , 32 , 33 ] have been studied, with the majority showing exceptional prediction outcome, although few have been validated in a real clinical setting. Recently, there has been research into computer aided interpretation, radiomics and machine learning to optimise the treatment decisions for spinal metastasis using multimodal imaging [ 34 ].…”