霍夫变换
人工智能
集合(抽象数据类型)
二进制数
计算机视觉
计算机科学
模式识别(心理学)
数据集
数学
图像(数学)
算术
程序设计语言
作者
Furen Xiao,I-Jen Chiang,Jau‐Min Wong,Yi-Hsin Tsai,Ke-Chun Huang,Chun-Chih Liao
标识
DOI:10.1016/j.compbiomed.2011.06.011
摘要
Midline shift (MLS) is an important quantitative feature clinicians use to evaluate the severity of brain compression by various pathologies. The midline consists of many anatomical structures including the septum pellucidum (SP), a thin membrane between the frontal horns (FH) of the lateral ventricles. We proposed a procedure that can measure MLS by recognizing the SP within the given CT study. The FH region is selected from all ventricular regions by expert rules and the multiresolution binary level set method. The SP is recognized using Hough transform, weighted by repeated morphological erosion. Our system is tested on images from 80 patients admitted to the neurosurgical intensive care unit. The results are evaluated by human experts. The mean difference between automatic and manual MLS measurements is 0.23 ± 0.52 mm. Our method is robust and can be applied in emergency and routine settings.
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