PURPOSE: Ultrasound offers a safe radiation-free approach to visualize the spine and measure or assess scoliosis. However, ultrasound assessment also poses major challenges. We propose a real-time algorithm and software implementation to automatically delineate the posterior surface patches of transverse processes in tracked ultrasound; a necessary step toward the ultimate goal of spinal curvature measurement.
METHODS: Following a pre-filtering of each captured ultrasound image, the shadows cast by each transverse process bone is examined and contours which are likely posterior bone surface are kept. From these contours, a threedimensional volume of the bone surfaces is created in real-time as the operator acquires the images. The processing algorithm was implemented on the PLUS and 3D Slicer open-source software platforms.
RESULTS: The algorithm was tested with images captured using the SonixTouch ultrasound scanner, Ultrasonix C5-2 curvilinear transducer and NDI trakSTAR electromagnetic tracker. Ultrasound data was collected from patients presenting with idiopathic adolescent scoliosis. The system was able to produce posterior surface patches of the transverse process in real-time, as the images were acquired by a non-expert sonographer. The resulting transverse process surface patches were compared with manual segmentation by an expert. The average Hausdorff distance was 3.0 mm when compared to the expert segmentation.
CONCLUSION: The resulting surface patches are expected to be sufficiently accurate for driving a deformable registration between the ultrasound space and a generic spine model, to allow for three-dimensional visualization of the spine and measuring its curvature.
PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks such as transverse processes, but as bones have reduced visibility in ultrasound imaging, skeletal landmarks are typically segmented manually, which is an exceedingly laborious and long process. We propose an automatic algorithm to segment and localize the surface of bony areas in the transverse process for scoliosis in ultrasound.
METHODS: The algorithm uses cascade of filters to remove low intensity pixels, smooth the image and detect bony edges. By applying first differentiation, candidate bony areas are classified. The average intensity under each area has a correlation with the possibility of a shadow, and areas with strong shadow are kept for bone segmentation. The segmented images are used to reconstruct a 3-D volume to represent the whole spinal structure around the transverse processes. RESULTS: A comparison between the manual ground truth segmentation and the automatic algorithm in 50 images showed 0.17 mm average difference. The time to process all 1,938 images was about 37 Sec. (0.0191 Sec. / Image), including reading the original sequence file.
CONCLUSION: Initial experiments showed the algorithm to be sufficiently accurate and fast for segmentation transverse processes in ultrasound for spinal curvature measurement. An extensive evaluation of the method is currently underway on images from a larger patient cohort and using multiple observers in producing ground truth segmentation.
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