title: Improved Hessian multiscale enhancement filter.
abstract: Traditional Hessian multiscale filter consider only the local geometric feature but not the global grayscale information. In medical image analysis, Hessian filter is usually used to enhance the blood vessels. However, it also produces some pseudo vascular structures or some isolate noise points, such as the nasal soft tissues that have the similar shape with the vessels in MRA data, which will increase the difficulty of cerebrovascular segmentation. To resolve this issue, an improved Hessian multiscale filter is proposed in this paper. An image grayscale factor is added to the vascular similarity function computed by Hessian matrix eigenvalue. This method is experimented on brain MRA data and lung CTA data. Experimental results show that this method can enhance vascular structures, and simultaneously reduce the appearance of the pseudo vascular structures and the isolated noise points.
authors.affiliation: Key Laboratory of Medical Image Computing of Northeastern University, Ministry of Education, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
authors.forename: Jinzhu
authors.initials: J
authors.lastname: Yang
authors.affiliation: Key Laboratory of Medical Image Computing of Northeastern University, Ministry of Education, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
authors.forename: Shuang
authors.initials: S
authors.lastname: Ma
authors.affiliation: Neusoft, Shenyang 110819, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Sun
authors.affiliation: Key Laboratory of Medical Image Computing of Northeastern University, Ministry of Education, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
authors.forename: Wenjun
authors.initials: W
authors.lastname: Tan
authors.affiliation: Key Laboratory of Medical Image Computing of Northeastern University, Ministry of Education, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
authors.forename: Mengjia
authors.initials: M
authors.lastname: Xu
authors.affiliation: Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.
authors.forename: Nan
authors.initials: N
authors.lastname: Chen
authors.affiliation: Key Laboratory of Medical Image Computing of Northeastern University, Ministry of Education, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
authors.forename: Dazhe
authors.initials: D
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D002536:Cerebral Arteries / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D011651:Pulmonary Artery / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: CT image; Hessian filter; MRA image; grayscale; multiscale enhancement