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Two novel methods for automated quantification of total lesion burden in multiple sclerosis patients using multi-spectral magnetic resonance (MR) imaging ...
Two novel methods for automated quantification of total lesion burden in multiple sclerosis patients using multi-spectral magnetic resonance (MR) imaging ...
Dec 9, 2019 · Automated methods for lesion quantification, if accurate enough, hold the potential to make the detection of new and enlarged lesions consistent ...
Results: 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 ...
Missing: validation study.
We developed and validated a semi-automated method to quantify lesion volume changes. •. The method has excellent reproducibility and overall good accuracy.
Oct 19, 2023 · Here, we report a case-level sensitivity of 93.3%, relative to a consensus ground truth, for detecting MS disease activity in multi-center, real ...
Here, we present a computer-aided-detection (CAD) approach that uses machine learning techniques to detect changes in white matter brain lesions on MRI scans of ...
Several computer-assisted techniques for measuring multiple sclerosis lesion load on MR images have been developed to provide a quantitative and sensitive ...
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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 ...
Dec 17, 2019 · Deep learning may be a viable alternative to gadolinium-based contrast agents for identifying enhancing lesions in multiple sclerosis on MRI ...