Automatic Model-guided Segmentation of the Human Brain Ventricular System From CT Images

Rationale and Objectives Accurate segmentation of the brain ventricular system on computed tomographic (CT) imaging is useful in neurodiagnosis and neurosurgery. Manual segmentation is time consuming, usually not reproducible, and subjective. Because of image noise, low contrast between soft tissues...

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Veröffentlicht in:	Academic radiology 2010-06, Vol.17 (6), p.718-726
Hauptverfasser:	Liu, Jimin, PhD, Huang, Su, MS, Ihar, Volkau, PhD, Ambrosius, Wojciech, MD, Lee, Looi Chow, BS, Nowinski, Wieslaw L., PhD
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence brain ventricular system Cerebral Ventricles Cerebral Ventriculography - methods deformable region of interest Humans image segmentation Pattern Recognition, Automated - methods Radiographic Image Enhancement - methods Radiographic Image Interpretation, Computer-Assisted - methods Radiology Reproducibility of Results Sensitivity and Specificity stroke Tomography, X-Ray Computed - methods
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