ISSN (Online): 2348-991X | ISSN (Print): 2454-9576
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Research Article
Open Access

The Application of Artificial Intelligence Technology for analysing MRI images of uterine fibroids – the difficulties and limitations

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DOI: 10.18535/ijmsci/v11i7.02· Pages: 7185-7191· Vol. 11, No. 07, (2024)· Published: July 15, 2024
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Abstract

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 focussed 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 analyse, 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 analyse MRI images and incorporate AI into their daily imaging work.

Keywords

Magnetic Resonance ImagingMRIArtificial IntelligenceAIuterine fibroidssegmentationdeep learningdeep neural networksDNNsconvolutional neural networkCNNTransformer
Author details
Felix Wong
NICM Health Research Institute, Western Sydney University, Sydney, NSW, Australia
✉ Corresponding Author
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Wu Shun
NICM Health Research Institute, Western Sydney University, Sydney, NSW, Australia
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