Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK; Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK.
Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK; Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK.
Med Image Anal. 2017 May;38:50-64. doi: 10.1016/j.media.2017.02.007. Epub 2017 Feb 24.
Although white matter hyperintensities evolve in the course of ageing, few solutions exist to consider the lesion segmentation problem longitudinally. Based on an existing automatic lesion segmentation algorithm, a longitudinal extension is proposed. For evaluation purposes, a longitudinal lesion simulator is created allowing for the comparison between the longitudinal and the cross-sectional version in various situations of lesion load progression. Finally, applied to clinical data, the proposed framework demonstrates an increased robustness compared to available cross-sectional methods and findings are aligned with previously reported clinical patterns.
尽管脑白质高信号在衰老过程中不断演变，但目前几乎没有解决方案可以考虑对其进行纵向的病灶分割问题。基于现有的自动病灶分割算法，提出了一种纵向扩展。为了评估目的，创建了一个纵向病灶模拟器，允许在不同的病灶负荷进展情况下对纵向和横向版本进行比较。最后，将该框架应用于临床数据，与现有的横向方法相比，该框架表现出更高的鲁棒性，研究结果与先前报道的临床模式一致。
