Comparison of two- and three-dimensional filtering methods to improve image quality in multiplanar.pdf

TECHNICAL REPORT Comparison of two- and three-dimensional filtering methods to improve image quality in multiplanar reconstruction of cone-beam computed tomography Morihisa Sagawa ? Yasutaka Miyoseta ? Yoshihiko Hayakawa ? Akira Honda Received: 21 August 2009 / Accepted: 14 September 2009 / Published online: 27 October 2009
Japanese Society for Oral and Maxillofacial Radiology and Springer 2009 Abstract Objectives Two- and three-dimensional (2D and 3D, respectively) filtering methods were examined to improve the accuracy of bone morphology depicted in dental cone- beam computed tomography (CBCT) images. An attempt to improve multiplanar reconstruction (MPR) image qual- ity was carried out by reducing the image noise. Methods CBCT examinations were performed with the following principal exposure parameters: I-mode, FOV 10 cm in diameter, 120 kV, 15 mA, 0.2 mm slice thick- ness, and exposure time of 10 s. 2D and 3D filtering pro- cedures for averaging, median smoothing, and Gaussian smoothing were applied for improvement of MPR images. For comparison, 2D and 3D Laplacian sharpening for images preprocessed by Gaussian sharpening was also tested. Results MPR images at the midsagittal plane on the maxilla are presented. Three smoothing filters yielded improvements in slightly different ways. The Gaussian filter clearly showed moderate changes. Small but obvious differences were observed between 2D and 3D filtering. When we focused on the depiction of bone contours, the effects of these noise reduction filters seemed to be mini- mal in morphological bone depiction. The Laplacian filter was useful for sharpening and emphasized noise in the resulting images, in contrast to those processed by smoothing filters. Conclusions Various smoothing filtering methods reduced the noise on MPR images of CBCT and also functioned differently between 2D and 3D filtering matrices. Keywords Computed tomography, cone beam
Digital filtration
Smoothing filter Introduction Cone-beam compu