title: Automatic detection and quantification of brain midline shift using anatomical marker model.
abstract: Brain midline shift (MLS) is a significant factor in brain CT diagnosis. In this paper, we present a new method of automatically detecting and quantifying brain midline shift in traumatic injury brain CT images. The proposed method automatically picks out the CT slice on which midline shift can be observed most clearly and uses automatically detected anatomical markers to delineate the deformed midline and quantify the shift. For each anatomical marker, the detector generates five candidate points. Then the best candidate for each marker is selected based on the statistical distribution of features characterizing the spatial relationships among the markers. Experiments show that the proposed method outperforms previous methods, especially in the cases of large intra-cerebral hemorrhage and missing ventricles. A brain CT retrieval system is also developed based on the brain midline shift quantification results.
authors: School of Computing, National University of Singapore, Singapore.
authors: Ruizhe
authors: R
authors: Liu
authors: Institute for Infocomm Research, Singapore.
authors: Shimiao
authors: S
authors: Li
authors: Institute for Infocomm Research, Singapore. Electronic address: subl@i2r.a-star.edu.sg.
authors: Bolan
authors: B
authors: Su
authors: School of Computing, National University of Singapore, Singapore.
authors: Chew Lim
authors: CL
authors: Tan
authors: School of Computing, National University of Singapore, Singapore.
authors: Tze-Yun
authors: TY
authors: Leong
authors: National Neuroscience Institute, Tan Tock Seng Hospital, Singapore.
authors: Boon Chuan
authors: BC
authors: Pang
authors: National Neuroscience Institute, Tan Tock Seng Hospital, Singapore.
authors: C C Tchoyoson
authors: CC
authors: Lim
authors: National Neuroscience Institute, Tan Tock Seng Hospital, Singapore.
authors: Cheng Kiang
authors: CK
authors: Lee
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000000981:diagnostic imaging*; D001921:Brain / Q000000981:diagnostic imaging*; D020201:Brain Hemorrhage, Traumatic / Q000000981:diagnostic imaging*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Anatomatic marker model; Brain CT diagnosis; Brain midline shift; Midline shift detection and quantification