Paper
17 March 2015 Quantification of cerebral ventricle volume change of preterm neonates using 3D ultrasound images
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Abstract
Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates. Quantitative measurement of ventricular dilation or shrinkage is important for monitoring patients and in evaluation of treatment options. 3D ultrasound (US) has been used to monitor the ventricle volume as a biomarker for ventricular dilation. However, volumetric quantification does not provide information as to where dilation occurs. The location where dilation occurs may be related to specific neurological problems later in life. For example, posterior horn enlargement, with thinning of the corpus callosum and parietal white matter fibres, could be linked to poor visuo-spatial abilities seen in hydrocephalic children. In this work, we report on the development and application of a method used to analyze local surface change of the ventricles of preterm neonates with IVH from 3D US images. The technique is evaluated using manual segmentations from 3D US images acquired in two imaging sessions. The surfaces from baseline and follow-up were registered and then matched on a point-by-point basis. The distance between each pair of corresponding points served as an estimate of local surface change of the brain ventricle at each vertex. The measurements of local surface change were then superimposed on the ventricle surface to produce the 3D local surface change map that provide information on the spatio-temporal dilation pattern of brain ventricles following IVH. This tool can be used to monitor responses to different treatment options, and may provide important information for elucidating the deficiencies a patient will have later in life.
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Yimin Chen, Jessica Kishimoto, Wu Qiu, Sandrine de Ribaupierre M.D., Aaron Fenster, and Bernard Chiu "Quantification of cerebral ventricle volume change of preterm neonates using 3D ultrasound images", Proc. SPIE 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography, 94190V (17 March 2015); https://doi.org/10.1117/12.2081470
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
3D image processing

Image segmentation

Ultrasonography

3D metrology

3D acquisition

Brain

3D applications

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