Automatic recognition of vertebral landmarks in fluoroscopic sequences for analysis of intervertebral kinematics

被引:28
|
作者
Bifulco, P [1 ]
Cesarelli, M
Allen, R
Sansone, M
Bracale, M
机构
[1] Univ Naples Federico II, Dept Elect & Telecommun Engn, Biomed Engn Unit, Naples, Italy
[2] Univ Southampton, Inst Sound & Vibrat Res, Southampton SO9 5NH, Hants, England
关键词
intervertebral kinematics; vertebral segments; motion analysis; fluoroscopy; time-varying image processing;
D O I
10.1007/BF02345268
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Intervertebral kinematics closely relates to the functionality of the spinal segments, Direct measurement of the intervertebral kinematics in vivo is very problematic. The use of a fluoroscopic device can provide continuous screening of the lumbar tract during patient spontaneous motion, with an acceptable, low X-ray dose. The kinematic analysis is intended to be limited to planar motion, Kinematic parameters are computed from vertebral landmarks on each frame of the image sequence. Landmarks are normally selected manually in spite of the fact that this is subjective, tedious to perform and regarded as one of the major contributors to errors in the computed kinematic parameters. The aim of this work is to present an innovative method for the automatic recognition of vertebral landmarks throughout a fluoroscopic image sequence to provide an objective and more precise quantification of intervertebral kinematics. The recognition procedure is based upon comparing vertebral features in two adjacent frames by means of a cross-correlation index, which is also robust despite the low signal-to-noise ratio of the lumbar fluoroscopic images. To provide a quantitative assessment of this method a calibration model was used which consisted of two lumbar vertebrae linked by a universal joint. The reliability and accuracy of the kinematic measurements have been investigated. The errors are of the order of a millimetre for the localisation of the intervertebral centre of rotation and tenths of a degree for the intervertebral angle. Error analysis suggests that this method improves the accuracy of the intervertebral kinematic calculations and has the potential to automate the selection of anatomical landmarks.
引用
收藏
页码:65 / 75
页数:11
相关论文
共 50 条
  • [1] Automatic recognition of vertebral landmarks in fluoroscopic sequences for analysis of intervertebral kinematics
    P. Bifulco
    M. Cesarelli
    R. Allen
    M. Sansone
    M. Bracale
    Medical and Biological Engineering and Computing, 2001, 39 : 65 - 75
  • [2] Automatic quantification of lumbar vertebral kinematics from dynamic fluoroscopic sequences
    Camp, Jon
    Zhao, Kristin
    Morel, Etienne
    White, Dan
    Magnuson, Dixon
    Gay, Ralph
    An, Kai-Nan
    Robb, Richard
    MEDICAL IMAGING 2009: COMPUTER-AIDED DIAGNOSIS, 2009, 7260
  • [3] Automatic Detection of Cervical Vertebral Landmarks for Fluoroscopic Joint Motion Analysis
    Jakobsen, Ida Marie Groth
    Plocharski, Maciej
    IMAGE ANALYSIS, 2019, 11482 : 209 - 220
  • [4] Sacral Vertebral Augmentation: Confirmation of Fluoroscopic Landmarks by Open Dissection
    Betts, Andres
    PAIN PHYSICIAN, 2008, 11 (01) : 57 - 65
  • [5] Automatic recognition of cephalometric landmarks.
    Tanikawa, C.
    Yagi, M.
    Shibata, T.
    Takada, K.
    JOURNAL OF DENTAL RESEARCH, 2003, 82 : B166 - B166
  • [6] Automatic Inference and Measurement of 3D Carpal Bone Kinematics From Single View Fluoroscopic Sequences
    Chen, Xin
    Graham, Jim
    Hutchinson, Charles
    Muir, Lindsay
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2013, 32 (02) : 317 - 328
  • [7] Automatic extraction of vertebral landmarks from ultrasound images
    Brignol, Arnaud
    Cheriet, Farida
    Laporte, Catherine
    M S-MEDECINE SCIENCES, 2021, 37 : 22 - 24
  • [8] Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach
    Jamaludin, Amir
    Lootus, Meelis
    Kadir, Timor
    Zisserman, Andrew
    COMPUTATIONAL METHODS AND CLINICAL APPLICATIONS FOR SPINE IMAGING, CSI 2015, 2016, 9402 : 97 - 103
  • [9] Automatic Tracking of Cervical Spine using Fluoroscopic Sequences
    Nauman, Muhammad
    Hassan, Ali
    Riaz, Farhan
    Rehman, Saad
    Nedergard, Rasmus Wiberg
    Holt, Kelly
    Haavik, Heidi
    Niazi, Imran Khan
    PROCEEDINGS OF THE 2017 INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS), 2017, : 592 - 598
  • [10] Automatic recognition of landmarks on digital dental models
    Woodsend, Brenainn
    Koufoudaki, Eirini
    Mossey, Peter A.
    Lin, Ping
    COMPUTERS IN BIOLOGY AND MEDICINE, 2021, 137