Afzal H M Rehan, Luo Suhuai, Ramadan Saadallah, Lechner-Scott Jeannette
School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia/Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia.
Mult Scler. 2022 May;28(6):849-858. doi: 10.1177/1352458520966298. Epub 2020 Oct 28.
Computer-aided diagnosis can facilitate the early detection and diagnosis of multiple sclerosis (MS) thus enabling earlier interventions and a reduction in long-term MS-related disability. Recent advancements in the field of artificial intelligence (AI) have led to the improvements in the classification, quantification and identification of diagnostic patterns in medical images for a range of diseases, in particular, for MS. Importantly, data generated using AI techniques are analyzed automatically, which compares favourably with labour-intensive and time-consuming manual methods.
The aim of this review is to assist MS researchers to understand current and future developments in the AI-based diagnosis and prognosis of MS.
We will investigate a variety of AI approaches and various classifiers and compare the current state-of-the-art techniques in relation to lesion segmentation/detection and prognosis of disease. After briefly describing the magnetic resonance imaging (MRI) techniques commonly used, we will describe AI techniques used for the detection of lesions and MS prognosis.
We then evaluate the clinical maturity of these AI techniques in relation to MS.
Finally, future research challenges are identified in a bid to encourage further improvements of the methods.
计算机辅助诊断有助于早期发现和诊断多发性硬化症（MS），从而实现早期干预并减少与MS相关的长期残疾。人工智能（AI）领域的最新进展已使一系列疾病（尤其是MS）的医学图像诊断模式在分类、量化和识别方面得到改进。重要的是，使用AI技术生成的数据会自动进行分析，这比劳动强度大且耗时的手动方法更具优势。
本综述的目的是帮助MS研究人员了解基于AI的MS诊断和预后的当前及未来发展。
我们将研究各种AI方法和不同的分类器，并比较当前在病变分割/检测和疾病预后方面的最先进技术。在简要描述常用的磁共振成像（MRI）技术后，我们将描述用于病变检测和MS预后的AI技术。
然后，我们评估这些AI技术在MS方面的临床成熟度。
最后，确定未来的研究挑战，以鼓励进一步改进这些方法。
