AUTOMATED VENTRICLE PARCELLATION AND EVAN'S RATIO COMPUTATION IN PRE- AND POST-SURGICAL VENTRICULOMEGALY.
AUTOMATED VENTRICLE PARCELLATION AND EVAN'S RATIO COMPUTATION IN PRE- AND POST-SURGICAL VENTRICULOMEGALY.
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DOI：
10.1109/isbi53787.2023.10230729
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发表时间：
2023-04
期刊：
影响因子：
--
通讯作者：
Prince, Jerry L.
中科院分区：
文献类型：
--
作者：
Wang, Yuli;Feng, Anqi;Xue, Yuan;Zuo, Lianrui;Liu, Yihao;Blitz, Ari M.;Luciano, Mark G.;Carass, Aaron;Prince, Jerry L.
常压性脑积水（NPH）是一种脑室增大和多种认知和运动症状相关的脑部疾病。心室增大的程度可以用磁共振成像（mri）来测量，用埃文比（ER）来定量表征。需要自动计算ER，以避免与MRI手动测量相关的额外时间和变化。由于分流手术经常用于治疗NPH，因此该过程必须对分流术和相关植入物引起的图像伪影具有鲁棒性。在本文中，我们提出了一个三维兴趣区域感知（roi感知）网络分割心室。该方法在术前核磁共振成像和术后带伪影的核磁共振成像上都达到了最先进的性能。基于我们的分割结果，我们还描述了一种从这些结果计算ER的自动化方法。在多个数据集上的实验结果证明了该方法在协助临床医生诊断和管理NPH方面的潜力。
Normal pressure hydrocephalus (NPH) is a brain disorder associated with enlarged ventricles and multiple cognitive and motor symptoms. The degree of ventricular enlargement can be measured using magnetic resonance images (MRIs) and characterized quantitatively using the Evan’s ratio (ER). Automatic computation of ER is desired to avoid the extra time and variations associated with manual measurements on MRI. Because shunt surgery is often used to treat NPH, it is necessary that this process be robust to image artifacts caused by the shunt and related implants. In this paper, we propose a 3D regions-of-interest aware (ROI-aware) network for segmenting the ventricles. The method achieves state-of-the-art performance on both pre-surgery MRIs and post-surgery MRIs with artifacts. Based on our segmentation results, we also describe an automated approach to compute ER from these results. Experimental results on multiple datasets demonstrate the potential of the proposed method to assist clinicians in the diagnosis and management of NPH.
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