Multifiber pathway reconstruction using bundle constrained streamline.
Fiber tractography techniques in diffusion magnetic resonance imaging have become a primary tool for studying the fiber architecture of biological tissues both noninvasively and in vivo. Streamline tracking, as a simple and efficient tractography technique, is widely used to reconstruct fiber pathways. It is however very sensitive to noisy estimation of local fiber orientations. In this paper, we propose a bundle constrained streamline method to accurately reconstruct multifiber pathways. The method introduces neighboring fiber consistency constraint in the tracking process and reconstructs fiber pathways that have optimal tradeoff between consistency with local fiber orientation estimations and similarity with neighboring fiber segment orientations. Results on synthetic, physical phantom and real human brain DW images show that the proposed method allows regular fiber pathways to be reconstructed and outperforms existing techniques.
Metislab, Harbin Institute of Technology, Harbin, China; CREATIS, CNRS UMR 5220, Inserm U1044, INSA Lyon, University of Lyon, Villeurbanne, France. Electronic address: chuchunyu@hit.edu.cn.
Chun-Yu
CY
Chu
Metislab, Harbin Institute of Technology, Harbin, China; CREATIS, CNRS UMR 5220, Inserm U1044, INSA Lyon, University of Lyon, Villeurbanne, France.
Jian-Ping
JP
Huang
CREATIS, CNRS UMR 5220, Inserm U1044, INSA Lyon, University of Lyon, Villeurbanne, France.
Chang-Yu
CY
Sun
Metislab, Harbin Institute of Technology, Harbin, China.
Yan-Li
YL
Zhang
Metislab, Harbin Institute of Technology, Harbin, China; CREATIS, CNRS UMR 5220, Inserm U1044, INSA Lyon, University of Lyon, Villeurbanne, France. Electronic address: liu.wanyu@gmail.com.
Wan-Yu
WY
Liu
Metislab, Harbin Institute of Technology, Harbin, China; CREATIS, CNRS UMR 5220, Inserm U1044, INSA Lyon, University of Lyon, Villeurbanne, France.
Yue-Min
YM
Zhu
D000465:Algorithms; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D000069550:Machine Learning; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity; D066127:White Matter / Q000033:anatomy & histology*