Zhenyu Tang1, Josef Pauli. 1. Universität Duisburg-Essen Fakultät für Ingenieurwissenschaften Abteilung für Informatik und Angewandte Kognitionswissenschaft, 47048 Duisburg, Germany. zhenyu.tang@uni-due.de
Abstract
PURPOSE: A fully automatic method is proposed for extracting human spine curve which is required for gait modeling. By means of the gait modeling, origin of the gait pathology of patients could be found. METHODS: Our method is composed of two parts. The first part is the extraction of intervertebral disk positions where an efficient method is proposed. At the beginning of this part, all possible positions of intervertebral disks are located using a gradient-based method. Then, non-intervertebral disks are filtered out by a graph-based and an active shape model-based methods. In the second part, extracted disk positions are used by a vertebra registration method to segment spine vertebrae. Finally, spine curve is obtained by interpolating centers of segmented vertebrae using cubic spline. RESULTS: We tested our method with 13 MR data sets of patients. All disk positions of each MR data set were correctly extracted in the first part. The mean deviation of centers of segmented vertebrae that were obtained in the second part and used to interpolate spine curve was around 1.4 mm. CONCLUSIONS: Our method achieves a fully automatic extraction of the spine curve. The extraction of intervertebral disk positions in the first part of our method when compared to model-based methods and manual selection which were proposed in other papers is highly efficient. In the second part including the vertebra registration, a new similarity measurement method, which is used to guide the vertebra atlas fitting process, is proposed to solve the problem of changes in overlap. Through our experiment, results of spine curves are at a highly accurate level.
PURPOSE: A fully automatic method is proposed for extracting human spine curve which is required for gait modeling. By means of the gait modeling, origin of the gait pathology of patients could be found. METHODS: Our method is composed of two parts. The first part is the extraction of intervertebral disk positions where an efficient method is proposed. At the beginning of this part, all possible positions of intervertebral disks are located using a gradient-based method. Then, non-intervertebral disks are filtered out by a graph-based and an active shape model-based methods. In the second part, extracted disk positions are used by a vertebra registration method to segment spine vertebrae. Finally, spine curve is obtained by interpolating centers of segmented vertebrae using cubic spline. RESULTS: We tested our method with 13 MR data sets of patients. All disk positions of each MR data set were correctly extracted in the first part. The mean deviation of centers of segmented vertebrae that were obtained in the second part and used to interpolate spine curve was around 1.4 mm. CONCLUSIONS: Our method achieves a fully automatic extraction of the spine curve. The extraction of intervertebral disk positions in the first part of our method when compared to model-based methods and manual selection which were proposed in other papers is highly efficient. In the second part including the vertebra registration, a new similarity measurement method, which is used to guide the vertebra atlas fitting process, is proposed to solve the problem of changes in overlap. Through our experiment, results of spine curves are at a highly accurate level.
Authors: Stefan Schmidt; Jörg Kappes; Martin Bergtholdt; Vladimir Pekar; Sebastian Dries; Daniel Bystrov; Christoph Schnörr Journal: Inf Process Med Imaging Date: 2007
Authors: Sofia K Michopoulou; Lena Costaridou; Elias Panagiotopoulos; Robert Speller; George Panayiotakis; Andrew Todd-Pokropek Journal: IEEE Trans Biomed Eng Date: 2009-04-14 Impact factor: 4.538