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Longitudinal Analysis of Pre-Term Neonatal Cerebral Ventricles From 3D Ultrasound Images Using Spatial-Temporal Deformable Registration

机译:使用时空可变形配准从3D超声图像对早产新生儿脑室进行纵向分析

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Preterm neonates with a very low birth weight of less than 1,500 grams are at increased risk for developing intraventricular hemorrhage (IVH), which is a major cause of brain injury in preterm neonates. Quantitative measurements of ventricular dilatation or shrinkage play an important role in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular changes. However, ventricle volume as a global indicator does not allow for precise analysis of local ventricular changes, which could be linked to specific neurological problems often seen in the patient population later in life. In this work, a 3D+t spatial-temporal deformable registration approachis proposed, which is applied to the analysis of the detailed local changes of preterm IVH neonatal ventricles from 3D US images. In particular, a novel sequential convex/dual optimization algorithm is introduced to extract the optimal 3D+t spatial-temporal deformable field, which simultaneously optimizes the sequence of 3D deformation fieldswhile enjoying both efficiencyand simplicity in numerics. The developed registration technique was evaluated by comparing two manually extracted ventricle surfaces from the baseline and the registered follow-up images using the metrics of Dice similarity coefficient (DSC), mean absolute surface distance (MAD), and maximum absolute surface distance (MAXD). The performed experiments using 14 patients with 5 time-point images per patient show that the proposed 3D+t registration approach accurately recovered the longitudinal deformation of ventricle surfaces from 3D US images. The proposed approach may be potentially used to analyse the change pattern of cerebral ventricles of IVH patients, their response to different treatment options, and to elucidate the deficiencies that a patient could have later in life. To the best of our knowledge, this paper reports the first study on the longitudinalanalysis of neonatal ventricular system from 3D US images.
机译:出生体重不足1,500克的极低出生早产儿发生脑室内出血(IVH)的风险增加,这是早产新生儿脑损伤的主要原因。心室扩张或收缩的定量测量在监测患者和评估治疗方案中起着重要作用。已经开发了3D超声(美国)来监测心室容积,作为心室变化的生物标记。但是,作为整体指标的心室容积不能对局部心室变化进行精确分析,而这可能与以后在患者人群中经常看到的特定神经系统问题有关。在这项工作中,提出了一种3D + t时空变形的配准方法,该方法被用于分析3D US图像中早产IVH新生儿心室的详细局部变化。特别地,引入了新颖的顺序凸/对偶优化算法来提取最佳3D + t时空可变形场,其同时优化了3D变形场的序列,同时兼顾了数值的效率和简洁性。通过使用Dice相似系数(DSC),平均绝对表面距离(MAD)和最大绝对表面距离(MAXD)的度量标准,通过比较从基线和已注册的随访图像中两个手动提取的心室表面,评估了开发的注册技术。 。使用14位患者进行的实验(每位患者5个时间点图像)显示,提出的3D + t配准方法可从3D US图像准确恢复心室表面的纵向变形。所提出的方法可潜在地用于分析IVH患者脑室的变化模式,其对不同治疗方案的反应,并阐明患者以后可能出现的缺陷。据我们所知,本文首次报道了从3D美国图像对新生儿心室系统进行纵向分析的研究。

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