Removal of bone in CT angiography by multiscale matched mask bone elimination.

For clear visualization of vessels in CT angiography (CTA) images of the head and neck using maximum intensity projection (MIP) or volume rendering (VR) bone has to be removed. In the past we presented a fully automatic method to mask the bone [matched mask bone elimination (MMBE)] for this purpose. A drawback is that vessels adjacent to bone may be partly masked as well. We propose a modification, multiscale MMBE, which reduces this problem by using images at two scales: a higher resolution than usual for image processing and a lower resolution to which the processed images are transformed for use in the diagnostic process. A higher in-plane resolution is obtained by the use of a sharper reconstruction kernel. The out-of-plane resolution is improved by deconvolution or by scanning with narrower collimation. The quality of the mask that is used to remove bone is improved by using images at both scales. After masking, the desired resolution for the normal clinical use of the images is obtained by blurring with Gaussian kernels of appropriate widths. Both methods (multiscale and original) were compared in a phantom study and with clinical CTA data sets. With the multiscale approach the width of the strip of soft tissue adjacent to the bone that is masked can be reduced from 1.0 to 0.2 mm without reducing the quality of the bone removal. The clinical examples show that vessels adjacent to bone are less affected and therefore better visible. Images processed with multiscale MMBE have a slightly higher noise level or slightly reduced resolution compared with images processed by the original method and the reconstruction and processing time is also somewhat increased. Nevertheless, multiscale MMBE offers a way to remove bone automatically from CT angiography images without affecting the integrity of the blood vessels. The overall image quality of MIP or VR images is substantially improved relative to images processed with the original MMBE method.

[1]  U. Baum,et al.  Computed tomography angiography versus digital subtraction angiography in vascular mapping for planning of microsurgical reconstruction of the mandible , 2005, European Radiology.

[2]  H. Venema,et al.  Removal of bone in CT angiography of the cervical arteries by piecewise matched mask bone elimination. , 2004, Medical physics.

[3]  H. Venema,et al.  Multisection CT venography of the dural sinuses and cerebral veins by using matched mask bone elimination. , 2004, AJNR. American journal of neuroradiology.

[4]  Krishna Subramanyan,et al.  Automatic bone removal in CT angiography , 2005 .

[5]  G D Rubin,et al.  CT angiography with spiral CT and maximum intensity projection. , 1992, Radiology.

[6]  M S van Leeuwen,et al.  CT angiography: source images and postprocessing techniques in the detection of cerebral aneurysms. , 1997, AJR. American journal of roentgenology.

[7]  G Wang,et al.  Longitudinal image deblurring in spiral CT. , 1994, Radiology.

[8]  R. Alberico,et al.  Cerebral CT venography. , 1996, Radiology.

[9]  E Klotz,et al.  Bone-subtraction Ct Angiography for the Evaluation of Intracranial Aneurysms Materials and Methods , 2004 .

[10]  Arnold W. M. Smeulders,et al.  Scale Dependency of Image Derivatives for Feature Measurement in Curvilinear Structures , 2001, International Journal of Computer Vision.

[11]  M Fiebich,et al.  Automatic bone segmentation technique for CT angiographic studies. , 1999, Journal of computer assisted tomography.

[12]  Ge Wang,et al.  Spiral CT image deblurring for cochlear implantation , 1998, IEEE Transactions on Medical Imaging.

[13]  Rainer Raupach,et al.  Spatial domain filtering for fast modification of the tradeoff between image sharpness and pixel noise in computed tomography , 2003, IEEE Transactions on Medical Imaging.

[14]  H. Venema,et al.  Reproducibility of multi-slice spiral computed tomography scans: an experimental study. , 2004, Medical physics.

[15]  W. Bautz,et al.  Clinical evaluation of bone-subtraction CT angiography (BSCTA) in head and neck imaging , 2006, European Radiology.

[16]  E. Fishman,et al.  Automated bone editing algorithm for CT angiography: preliminary results. , 1996, AJR. American journal of roentgenology.

[17]  L. J. Thomas,et al.  Noise and Edge Artifacts in Maximum-Likelihood Reconstructions for Emission Tomography , 1987, IEEE Transactions on Medical Imaging.

[18]  H. Venema,et al.  CT angiography of the circle of Willis and intracranial internal carotid arteries: maximum intensity projection with matched mask bone elimination-feasibility study. , 2001, Radiology.

[19]  P. Joseph,et al.  A Method for Correcting Bone Induced Artifacts in Computed Tomography Scanners , 1978, Journal of computer assisted tomography.

[20]  R Kikinis,et al.  Common carotid artery bifurcation: evaluation with spiral CT. Work in progress. , 1992, Radiology.

[21]  A. Kaim,et al.  Cerebral veins: comparative study of CT venography with intraarterial digital subtraction angiography. , 1999, AJNR. American journal of neuroradiology.

[22]  P. Stieg,et al.  Evaluation of cerebral aneurysms with helical CT: correlation with conventional angiography and MR angiography. , 1994, Radiology.