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Multiple sclerosis (MS) is a serious disease typically occurring in the brain whose diagnosis and efficacy of treatment monitoring are vital. Magnetic resonance imaging (MRI) is frequently used in serial brain imaging due to the rich and detailed information provided.

Time-series analysis of images is widely used for MS diagnosis and patient follow-up. However, conventional manual methods are time-consuming, subjective, and error-prone. Thus, the development of automated techniques for the detection and quantification of MS lesions is a major challenge.

This paper presents an up-to-date review of the approaches which deal with the time-series analysis of brain MRI for detecting active MS lesions and quantifying lesion load change. We provide a comprehensive reference source for …