Title :
Double-Edge Detection of Radiographic Lumbar Vertebrae Images Using Pressurized Open DGVF Snakes
Author :
Kamalakannan, Sridharan ; Gururajan, Arunkumar ; Sari-Sarraf, Hamed ; Long, Rodney ; Antani, Sameer
Author_Institution :
Texas Tech Univ., Lubbock, TX, USA
fDate :
6/1/2010 12:00:00 AM
Abstract :
The detection of double edges in X-ray images of lumbar vertebrae is of prime importance in the assessment of vertebral injury or collapse that may be caused by osteoporosis and other spine pathology. In addition, if the above double-edge detection process is conducted within an automatic framework, it would not only facilitate inexpensive and fast means of obtaining objective morphometric measurements on the spine, but also remove the human subjectivity involved in the morphometric analysis. This paper proposes a novel force-formulation scheme, termed as pressurized open directional gradient vector flow snakes, to discriminate and detect the superior and inferior double edges present in the radiographic images of the lumbar vertebrae. As part of the validation process, this algorithm is applied to a set of 100 lumbar images and the detection results are quantified using analyst-generated ground truth. The promising nature of the detection results bears testimony to the efficacy of the proposed approach.
Keywords :
diagnostic radiography; medical image processing; analyst-generated ground truth; double-edge detection; force-formulation scheme; open directional gradient vector flow snakes; pressurized open DGVF snakes; radiographic lumbar vertebrae images; Directional gradient vector flow (DGVF) snakes; double edges; energy minimization; lumbar vertebrae; pressure force; Algorithms; Artificial Intelligence; Humans; Lumbar Vertebrae; Pattern Recognition, Automated; Pressure; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2010.2040082