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- W3211118399 endingPage "6843" @default.
- W3211118399 startingPage "6825" @default.
- W3211118399 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." @default.
- W3211118399 created "2021-11-08" @default.
- W3211118399 creator A5000799925 @default.
- W3211118399 creator A5027270375 @default.
- W3211118399 creator A5061305020 @default.
- W3211118399 creator A5068350940 @default.
- W3211118399 creator A5082472933 @default.
- W3211118399 date "2021-10-28" @default.
- W3211118399 modified "2023-09-25" @default.
- W3211118399 title "Emerging artificial intelligence applications in liver magnetic resonance imaging" @default.
- W3211118399 cites W1531911336 @default.
- W3211118399 cites W1575413653 @default.
- W3211118399 cites W1930624869 @default.
- W3211118399 cites W1968812902 @default.
- W3211118399 cites W1972516036 @default.
- W3211118399 cites W2000641576 @default.
- W3211118399 cites W2035186208 @default.
- W3211118399 cites W2059251195 @default.
- W3211118399 cites W2117539524 @default.
- W3211118399 cites W2117828918 @default.
- W3211118399 cites W2117892932 @default.
- W3211118399 cites W2165296488 @default.
- W3211118399 cites W2194775991 @default.
- W3211118399 cites W2204688218 @default.
- W3211118399 cites W2314336137 @default.
- W3211118399 cites W2507678479 @default.
- W3211118399 cites W2508053164 @default.
- W3211118399 cites W2534481205 @default.
- W3211118399 cites W2566230053 @default.
- W3211118399 cites W2567599812 @default.
- W3211118399 cites W2618530766 @default.
- W3211118399 cites W2619337392 @default.
- W3211118399 cites W2620296437 @default.
- W3211118399 cites W2620818159 @default.
- W3211118399 cites W2655445192 @default.
- W3211118399 cites W2754887662 @default.
- W3211118399 cites W2768270891 @default.
- W3211118399 cites W2773708607 @default.
- W3211118399 cites W2780795726 @default.
- W3211118399 cites W2793905111 @default.
- W3211118399 cites W2802798675 @default.
- W3211118399 cites W2805952202 @default.
- W3211118399 cites W2809844089 @default.
- W3211118399 cites W2894315883 @default.
- W3211118399 cites W2900204660 @default.
- W3211118399 cites W2904572485 @default.
- W3211118399 cites W2912360491 @default.
- W3211118399 cites W2915597952 @default.
- W3211118399 cites W2917616870 @default.
- W3211118399 cites W2919115771 @default.
- W3211118399 cites W2922744444 @default.
- W3211118399 cites W2934291851 @default.
- W3211118399 cites W2941219400 @default.
- W3211118399 cites W2941555836 @default.
- W3211118399 cites W2945147429 @default.
- W3211118399 cites W2945373215 @default.
- W3211118399 cites W2946513775 @default.
- W3211118399 cites W2949576325 @default.
- W3211118399 cites W2949721846 @default.
- W3211118399 cites W2960526884 @default.
- W3211118399 cites W2963037989 @default.
- W3211118399 cites W2963446712 @default.
- W3211118399 cites W2979640220 @default.
- W3211118399 cites W2998175747 @default.
- W3211118399 cites W2998990144 @default.
- W3211118399 cites W2999268284 @default.
- W3211118399 cites W2999356287 @default.
- W3211118399 cites W3001038816 @default.
- W3211118399 cites W3008117014 @default.
- W3211118399 cites W3012265814 @default.
- W3211118399 cites W3016023862 @default.
- W3211118399 cites W3018177167 @default.
- W3211118399 cites W3022403657 @default.
- W3211118399 cites W3024621125 @default.
- W3211118399 cites W3029385555 @default.
- W3211118399 cites W3033347459 @default.
- W3211118399 cites W3033352061 @default.
- W3211118399 cites W3035715385 @default.
- W3211118399 cites W3035739940 @default.
- W3211118399 cites W3035984306 @default.
- W3211118399 cites W3043838341 @default.
- W3211118399 cites W3047003037 @default.
- W3211118399 cites W3047439539 @default.
- W3211118399 cites W3083016620 @default.
- W3211118399 cites W3091776637 @default.
- W3211118399 cites W3098780148 @default.
- W3211118399 cites W3101381711 @default.
- W3211118399 cites W3103706824 @default.
- W3211118399 cites W3113920138 @default.
- W3211118399 cites W3129902266 @default.
- W3211118399 cites W3167347744 @default.
- W3211118399 cites W4239510810 @default.
- W3211118399 cites W4256314700 @default.
- W3211118399 doi "https://doi.org/10.3748/wjg.v27.i40.6825" @default.
- W3211118399 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8567471" @default.
- W3211118399 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34790009" @default.
- W3211118399 hasPublicationYear "2021" @default.
- W3211118399 type Work @default.