2014
DOI: 10.1155/2014/976323
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Image Segmentation and Analysis of Flexion-Extension Radiographs of Cervical Spines

Abstract: We present a new analysis tool for cervical flexion-extension radiographs based on machine vision and computerized image processing. The method is based on semiautomatic image segmentation leading to detection of common landmarks such as the spinolaminar (SL) line or contour lines of the implanted anterior cervical plates. The technique allows for visualization of the local curvature of these landmarks during flexion-extension experiments. In addition to changes in the curvature of the SL line, it has been fou… Show more

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Cited by 7 publications
(5 citation statements)
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“…There are various literatures towards segmentation problems that has also been considering different medical case study apart from lungs. Enikov and Anton [36] have used machine learning technique for segmenting images with cervical spines. Thresholding-based scheme was adopted by Wang et al [37] for faster process of medical image segmentation.…”
Section: Related Workmentioning
confidence: 99%
“…There are various literatures towards segmentation problems that has also been considering different medical case study apart from lungs. Enikov and Anton [36] have used machine learning technique for segmenting images with cervical spines. Thresholding-based scheme was adopted by Wang et al [37] for faster process of medical image segmentation.…”
Section: Related Workmentioning
confidence: 99%
“…It was reported that small wrist ganglion cysts (≤10 mm in the mean largest dimension) often appeared hypoechoic without posterior acoustic enhancement and did not fulfill the criteria for a simple cyst thus examiner’s experience is one of key factors for correct observation [ 6 , 7 ]. An automatic segmentation approach using intelligent computer vision techniques can mitigate such subjectivity in the image analysis [ 11 ]. Automatic segmentation in ultrasound images, however, can be difficult for numerous reasons such as insufficient contrast and resolution of image, speckle noise, which is inherent property of ultrasound imaging modality [ 12 ].…”
Section: Introductionmentioning
confidence: 99%
“…To avoid such subjectivity, we need an automatic image segmentation and identification tool for anatomical landmarks in the image analysis [11]. It is a difficult problem since the input image may not have sufficient contrast between target object and the background or it contains speckle noise, which is an inherent property of ultrasound imaging modality [12].…”
Section: Introductionmentioning
confidence: 99%