Automated boundary extraction of the spinal canal in MRI based on dynamic programming.
The spinal cord is the only communication link between the brain and the body. The abnormalities in it can lead to severe pain and sometimes to paralysis. Due to the growing gap between the number of available radiologists and the number of required radiologists, the need for computer-aided diagnosis and characterization is increasing. To ease this gap, we have developed a computer-aided diagnosis and characterization framework in lumbar spine that includes the spinal cord, vertebrae, and intervertebral discs. In this paper, we propose two spinal cord boundary extraction methods that fit into our framework based on dynamic programming in lumbar spine MRI. Our method incorporates the intensity of the image and the gradient of the image into a dynamic programming scheme and works in a fully-automatic fashion. The boundaries generated by our method is compared against reference boundaries in terms of Fréchet distance which is known to be a metric for shape analysis. The experimental results from 65 clinical data show that our method finds the spinal canal boundary correctly achieving a mean Fréchet distance of 13.5 pixels. For almost all data, the extracted boundary falls within the spinal cord. So, it can be used as a landmark when marking background regions and finding regions of interest.
Department of Computer Science and Engineering, University at Buffalo, SUNY, Buffalo, NY 14228, USA. jkoh@buffalo.edu
Jaehan
J
Koh
Vipin
V
Chaudhary
Gurmeet
G
Dhillon
D000465:Algorithms; D001331:Automation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D001330:Electronic Data Processing; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008159:Lumbar Vertebrae / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D013115:Spinal Canal / Q000473:pathology; D013116:Spinal Cord / Q000473:pathology*; D013168:Spondylolisthesis / Q000175:diagnosis