Automatic Bone Removal Research Articles

Image Quality Assessment of a Deep Learning-Based Automatic Bone Removal Algorithm for Cervical CTA.

The present study aims to evaluate the postprocessing image quality of a deep-learning (DL)-based automatic bone removal algorithm in the real clinical practice for cervical computed tomography angiography (CTA). A total of 100 patients (31 females, 61.4 ± 12.4 years old) who had performed cervical CTA from January 2022 to July 2022 were included retrospectively. Three different types of scanners were used. Ipsilateral cervical artery was divided into 10 segments. The performance of the DL algorithm and conventional algorithm in terms of bone removal and vascular integrity was independently evaluated by two radiologists for each segment. The difference in the performance between the two algorithms was compared. Inter- and intrarater consistency were assessed, and the correlation between the degree of carotid artery stenosis and the rank of bone removal and vascular integrity was analyzed. Significant differences were observed in the rankings of bone removal and vascular integrity between the two algorithms on most segments on both sides. Compared to DL algorithm, the conventional algorithm showed a higher correlation between the degree of carotid artery stenosis and vascular integrity (r = -0.264 vs r = -0.180). The inter- and intrarater consistency of DL algorithm were found to be higher than or equal to those of conventional algorithm. The DL algorithm for bone removal in cervical CTA demonstrated significantly better performance than conventional postprocessing method, particularly in the segments with complex anatomical structures and adjacent to bone.

A Deep Learning Approach for Automated Bone Removal from Computed Tomography Angiography of the Brain.

Advanced visualization techniques such as maximum intensity projection (MIP) and volume rendering (VR) are useful for evaluating neurovascular anatomy on CT angiography (CTA) of the brain; however, interference from surrounding osseous anatomy is common. Existing methods for removing bone from CTA images are limited in scope and/or accuracy, particularly at the skull base. We present a new brain CTA bone removal tool, which addresses many of these limitations.A deep convolutional neural network was designed and trained for bone removal using 72 brain CTAs. The model was tested on 15 CTAs from the same data source and 17 CTAs from an independent external dataset. Bone removal accuracy was assessed quantitatively, by comparing automated segmentation results to manual segmentations, and qualitatively by evaluating VR visualization of the carotid siphons compared to an existing method for automated bone removal.Average Dice overlap between automated and manual segmentations from the internal and external test datasets were 0.986 and 0.979 respectively. This was superior compared to a publicly available noncontrast head CT bone removal algorithm which had a Dice overlap of 0.947 (internal dataset) and 0.938 (external dataset). Our algorithm yielded better VR visualization of the carotid siphons than the publicly available bone removal tool in 14 out of 15 CTAs (93%, chi-square statistic of 22.5, p-value of < 0.00001) from the internal test dataset and 15 out of 17 CTAs (88%, chi-square statistic of 23.1, p-value of < 0.00001) from the external test dataset. Bone removal allowed subjectively superior MIP and VR visualization of vascular anatomy/pathology.The proposed brain CTA bone removal algorithm is rapid, accurate, and allows superior visualization of vascular anatomy and pathology compared to other available techniques and was validated on an independent external dataset.

A study on the usefulness of image reconstruction techniques of Brain CTA test using different kinds of workstation

목적: 본 연구는 두 개 내 동맥의 CT(Brain CT Angiography) 검사 후 감산 기법과 자동 뼈 제거 기법을 비교하여 영상의 진단적 차이에 대해 알아보고자 한다. 대상 및 방법: 3D 영상처리를 하기 위한 영상을 얻기 위해 256-slice CT를 사용하여 Brain CT Angiography를 검사한 30명의 영상을 이용하였다. 조영제 주입 전 영상과 조영제 주입 후 영상을 3D 영상 처리 장비 SyngoVia와 ISP에 전송하고, 각각 자체기능인 감산기법과 자동 뼈 제거기법을 이용하여 뼈를 제거하여 두 영상을 리커트 척도로 평가 하였다. 결과: SingoVia의 감산 기법을 이용한 영상이 총 평균 2.94점, ISP의 자동 뼈 제거 기법을 이용한 영상이 총 평균 2.57점으로 평가되었고, 최대강도투사에서 SyngoVia는 총 평균 2.93점, ISP는 총 평균 2.56점으로 평가되었다. 결론: CT검사 후 데이터를 이용하여 3D 영상 처리를 함에 있어 CT number값을 이용하여 조영 전 영상과 조영 후 영상을 적용하는 감산 기능을 이용하는 SyngoVia의 사용이 보다 유용한 영상을 표현해내는 것으로 나타났다.Purpose: The purpose of this study is to conduct CT scanning for intracranial artery and compare between subtraction technique and automatic bone removal technique to find out their diagnostic differences. Materials and Method: In order to acquire images for 3D processing, 256-slice brilliance iCT elite was used to generate brain CT angiography images from 30 patients.Pr e-images and post-images were sent to SyngoVia and ISP for 3D visualization, and each system used both subtraction and automatic bone removal techniques to remove the bones from the images.W e compared to image quality by Likert scale. Result: The total average scores of the created images were: 2.94 for the image from SingoVia’s subtraction technique, and 2.574 for the image from ISP’s automatic bone removal technique.T he total average scores from the maximum intensity projection were 2.93 for SyngoVia and 2.56 for ISP. This implies that 3D visualization of a source image which uses images with same parameters may result in imaging variations depending on what kind of 3D workstation is used.I t was not easy to remove the bones that are located close to blood vessels using ISP’s automatic bone removal technique and vessel loss was observed from some of the images. On the other hand, bones were easily removed with little vessel loss using SyngoVia’s subtraction technique. Conclusion: For 3D visualization of post-CT data, it was demonstrated that image expressions were more useful when created by SyngoVia’s subtraction technique using the CT number value to apply pre/post-images.

Dual-Energy CT in Children: Imaging Algorithms and Clinical Applications.

Dual-energy CT enables the simultaneous acquisition of CT images at two different x-ray energy spectra. By acquiring high- and low-energy spectral data, dual-energy CT can provide unique qualitative and quantitative information about tissue composition, allowing differentiation of multiple materials including iodinated contrast agents. The two dual-energy CT postprocessing techniques that best exploit the advantages of dual-energy CT in children are the material-decomposition images (which include virtual nonenhanced, iodine, perfused lung blood volume, lung vessel, automated bone removal, and renal stone characterization images) and virtual monoenergetic images. Clinical applications include assessment of the arterial system, lung perfusion, neoplasm, bowel diseases, renal calculi, tumor response to treatment, and metal implants. Of importance, the radiation exposure level of dual-energy CT is equivalent to or less than that of conventional single-energy CT. In this review, the authors discuss the basic principles of the dual-energy CT technologies and postprocessing techniques and review current clinical applications in the pediatric chest and abdomen.

I156] Why is dual energy CT (DECT) still not used widely in clinics?

Dual energy CT has been possible since last decade and has demonstrated considerable advantages in clinical diagnosis. DECT is achieved by ways that are unique to different CT platforms. DECT is considered as a first step towards achieving true “Spectral CT”. There are numerous applications including improved lesion detection and characterization, artifacts reduction and possible quantification of CT images. Advanced applications such as kidney stone classifications, gout detection, automatic bone removal, virtual non-contrast enhanced images and many others are routinely used clinically. In spite of these advantages, DECT is still not used widely in clinics. Factors includes multiple data sets, additional time for image processing, no financial incentives for reviewing multiple data sets of DECT compared to conventional CT data sets. This presentation will discuss the many factors that are holding this technology from wider acceptances.

Dual-energy bone removal computed tomography (BRCT): preliminary report of efficacy of acute intracranial hemorrhage detection.

One of the major applications of dual-energy computed tomography (DECT) is automated bone removal (BR). We hypothesized that the visualization of acute intracranial hemorrhage could be improved on BRCT by removing bone as it has the highest density tissue in the head. This preliminary study evaluated the efficacy of a DE BR algorithm for the head CT of trauma patients. Sixteen patients with acute intracranial hemorrhage within 1day after head trauma were enrolled in this study. All CT examinations were performed on a dual-source dual-energy CT scanner. BRCT images were generated using the Bone Removal Application. Simulated standard CT and BRCT images were visually reviewed in terms of detectability (presence or absence) of acute hemorrhagic lesions. DECT depicted 28 epidural/subdural hemorrhages, 17 contusional hemorrhages, and 7 subarachnoid hemorrhages. In detecting epidural/subdural hemorrhage, BRCT [28/28 (100%)] was significantly superior to simulated standard CT [17/28 (61%)] (p=.001). In detecting contusional hemorrhage, BRCT [17/17 (100%)] was also significantly superior to simulated standard CT [11/17 (65%)] (p=.0092). BRCT was superior to simulated standard CT in detecting acute intracranial hemorrhage. BRCT could improve the detection of small intracranial hemorrhages, particularly those adjacent to bone, by removing bone that can interfere with the visualization of small acute hemorrhage. In an emergency such as head trauma, BRCT can be used as support imaging in combination with simulated standard CT and bone scale CT, although BRCT cannot replace a simulated standard CT.

Dual-Energy Computed Tomography Angiography of the Head and Neck and Related Applications.

Dual-energy computed tomography (DECT) has become an increasingly widespread and useful component of the neuroimaging armamentarium, offering automated bone removal, metallic artifact reduction, and improved characterization of iodinated contrast enhancement. The application of these techniques to CT neuroangiography enables a number of benefits including more efficient 3D post-processing, contrast dose reduction opportunities, successful differentiation of hemorrhage from contrast staining following thromboembolic recanalization therapy, improved detection of active contrast extravasation in the setting of intracranial hemorrhage, and more precise characterization of atheromatous steno-occlusive disease.

Dual-Energy CT: New Horizon in Medical Imaging.

Dual-energy CT has remained underutilized over the past decade probably due to a cumbersome workflow issue and current technical limitations. Clinical radiologists should be made aware of the potential clinical benefits of dual-energy CT over single-energy CT. To accomplish this aim, the basic principle, current acquisition methods with advantages and disadvantages, and various material-specific imaging methods as clinical applications of dual-energy CT should be addressed in detail. Current dual-energy CT acquisition methods include dual tubes with or without beam filtration, rapid voltage switching, dual-layer detector, split filter technique, and sequential scanning. Dual-energy material-specific imaging methods include virtual monoenergetic or monochromatic imaging, effective atomic number map, virtual non-contrast or unenhanced imaging, virtual non-calcium imaging, iodine map, inhaled xenon map, uric acid imaging, automatic bone removal, and lung vessels analysis. In this review, we focus on dual-energy CT imaging including related issues of radiation exposure to patients, scanning and post-processing options, and potential clinical benefits mainly to improve the understanding of clinical radiologists and thus, expand the clinical use of dual-energy CT; in addition, we briefly describe the current technical limitations of dual-energy CT and the current developments of photon-counting detector.

Dual-Energy Computed Tomography Angiography of the Head and Neck With Single-Source Computed Tomography

Dual-energy computed tomographic angiography (DE-CTA) has been demonstrated to improve the visualization of the head and neck vessels. The aim of this study was to test the potential of split-filter single-source dual-energy CT to automatically remove bone from the final CTA data set. Dual-energy CTA was performed in 50 consecutive patients to evaluate the supra-aortic arteries, either to grade carotid artery stenosis or to rule out traumatic dissections. Dual-energy CTA was performed on a 128-slice single-source CT system equipped with a special filter array to separate the 120-kV spectrum into a high- and a low-energy spectrum for DE-based automated bone removal. Image quality of fully automated bone suppression and subsequent manual optimization was evaluated by 2 radiologists on maximum intensity projections using a 4-grade scoring system. The effect of image reconstruction with an iterative metal artifact reduction algorithm on DE postprocessing was tested using a 3-grade scoring system, and the time demand for each postprocessing step was measured. Two patients were excluded due to insufficient arterial contrast enhancement; in the remaining 48 patients, automated bone removal could be performed successfully. The addition of iterative metal artifact reduction algorithm improved image quality in 58.3% of the cases. After manual optimization, DE-CTA image quality was rated excellent in 7, good in 29, and moderate in 10 patients. Interobserver agreement was high (κ = 0.85). Stenosis grading was not influenced using DE-CTA with bone removal as compared with the original CTA. The time demand for DE image reconstruction was significantly higher than for single-energy reconstruction (42.1 vs 20.9 seconds). Our results suggest that bone removal in DE-CTA of the head and neck vessels with a single-source CT is feasible and can be performed within acceptable time and moderate user interaction.

Automatic bone removal for 3D TACE planning with C-arm CBCT: Evaluation of technical feasibility

Purpose To evaluate the technical feasibility of automatically removing the ribs and spine from C-arm cone-beam computed tomography (CBCT) images acquired during transcatheter arterial chemoembolization (TACE). Material and methods Fifty-eight patients (45.8 ± 5.0 years) with unresectable hepatocellular carcinoma (HCC) underwent transcatheter arterial chemoembolization and had intraprocedural CBCT imaging. Automatic bone removal was performed using model-based segmentation of the ventral cavity. Two interventional radiologists independently evaluated the performance of bone removal, remaining soft tissue retention, and general usability (where both the bone is appropriately removed while retaining soft tissue) for 3D TACE planning on a four-level (complete/excellent, adequate/good, incomplete/questionable, insufficient/bad) score. The proportion of inter-reader agreement was calculated. Results For ribs and spine removal, 98.3–100% and 100% of cases showed complete or adequate performance, respectively. In 96.6% of the cases, soft tissue was at least adequately retained. 91.3–93.1% of the cases demonstrated good or excellent general usability for TACE planning. Satisfactory inter-reader agreement proportion was achieved in ribs (93.1%) and spine removal (89.7%), soft tissue retention (84.5%), and general usability for TACE planning (72.4%). Conclusion Intraprocedural automatic bone removal on CBCT images is technically feasible and offers good removal of ribs and spine while preserving soft tissue. Its clinical value needs further assessment.

Abstract No. 439 - Clinical application of a new technique with automatic bone removal program for cbct imaging in TACE planning

Abstract No. 439 - Clinical application of a new technique with automatic bone removal program for cbct imaging in TACE planning

Automatic Bone Removal Technique in Whole-Body Dual-Energy CT Angiography: Performance and Image Quality

The purpose of this study was to evaluate the efficiency of automatic bone removal in dual-energy CT angiography (CTA) of the trunk. Nineteen patients underwent dual-energy CTA of the trunk (tube A, 140 kV; tube B, 100 kV). In addition to the dual-energy dataset, an image equivalent to that of a standard 120-kV single-energy examination was generated with both tubes. Automated bone segmentation was performed on both datasets, and the results were analyzed. The time required for and subjective image quality of the maximum intensity projections (MIPs) generated were evaluated. Errors in bone segmentation were found for 1.5% of bones on dual-energy images and 12.4% of bones on single-energy images (p < 0.01). The most important differences were found in the rib cage, sternum, and pelvis. The times required for postprocessing of MIPs were similar for the dual-energy (113.5 seconds) and single-energy (106.8 seconds) techniques. The subjective image quality of the arteries was considered better for dual-energy CTA (4.5 points) than for single-energy CTA (4.1 points) owing to false cutoff of vessels during the bone removal process on the single-energy images (p = 0.026). For CTA of the trunk, the dual-energy postprocessing capabilities for 3D visualization are superior to the threshold-based bone removal of single-energy CT. Dual-energy CTA can generate boneless MIP images of substantial quality.

Automated bone removal in CT angiography: Comparison of methods based on single energy and dual energy scans

To evaluate dual energy based methods for bone removal in computed tomography angiography (CTA) images and compare these with single energy based methods that use an additional, nonenhanced, CT scan. Four different bone removal methods were applied to CT scans of an anthropomorphic thorax phantom, acquired with a second generation dual source CT scanner. The methods differed by the way information on the presence of bone was obtained (either by using an additional, nonenhanced scan or by scanning with two tube voltages at the same time) and by the way the bone was removed from the CTA images (either by masking or subtracting the bone). The phantom contained parts which mimic vessels of various diameters in direct contact with bone. Both a quantitative and qualitative analysis of image quality after bone removal was performed. Image quality was quantified by the contrast-to-noise ratio (CNR) normalized to the square root of the dose (CNRD). At locations where vessels touch bone, the quality of the bone removal and the vessel preservation were visually assessed. The dual energy based methods were assessed with and without the addition of a 0.4 mm tin filter to the high voltage x-ray tube filtration. For each bone removal method, the dose required to obtain a certain CNR after bone removal was compared with the dose of a reference scan with the same CNR but without automated bone removal. The CNRD value of the reference scan was maximized by choosing the lowest tube voltage available. All methods removed the bone completely. CNRD values were higher for the masking based methods than for the subtraction based methods. Single energy based methods had a higher CNRD value than the corresponding dual energy based methods. For the subtraction based dual energy method, tin filtration improved the CNRD value with approximately 50%. For the masking based dual energy method, it was easier to differentiate between iodine and bone when tin filtration was applied. The CNRD value decreased only with 4% in that case. Compared to the dual scan based methods, the dual energy based methods had the advantage that only a single scan was made without the need of image registration. This might be easier to implement in clinical practice. Vessel preservation was better with bone subtraction than with bone masking. Smaller vessels were completely occluded by the bone mask. None of the bone removal methods was dose neutral. In general, dual scan based methods that use the lowest tube voltage available, have a higher CNR than the dual energy based approaches at the same dose level. Tin filtration improves the ability to differentiate between iodine and bone for the dual energy based masking method. In clinical practice, the advantages of the dual energy masking method might outweigh its disadvantage of a slightly higher dose penalty compared to the conventional dual scan masking method.

Automatic Bone Removal Dual-Energy CT Angiography for the Evaluation of Intracranial Aneurysms

To evaluate the diagnostic accuracy of dual-energy computed tomographic angiography (DE-CTA) in the detection of intracranial aneurysms and to determine whether DE-CTA provides adequate information to guide treatment choice. Eighty patients (31 men and 49 women; mean [SD] ages of 52 [9] years) with spontaneous subarachnoid hemorrhage underwent DE-CTA. The performance of DE-CTA was compared with conventional CTA created from average weighted images and digital subtraction angiography (DSA). Sensitivity and specificity for aneurysm detection were determined on a per-patient and per-aneurysm basis. The treatment choice was assessed on the basis of aneurysm neck size and/or the dome/neck ratio. With DSA as reference standard (n = 61; 47 aneurysms in 41 patients), DE-CTA correctly detected 45 aneurysms in 41 patients corresponding to sensitivity and specificity of 100% and 95.0% on a per-patient basis versus 95.7% and 95.0% on a per-aneurysm basis, whereas conventional CTA correctly detected 43 aneurysms in 39 patients corresponding to sensitivity and specificity of 95.1% and 95.0% on a per-patient basis versus 91.5% and 95.0% on a per-aneurysm basis. No statistical difference between DE-CTA and conventional CTA was found for the diagnostic evaluation of intracranial aneurysms. Surgery was performed to treat 38 aneurysms, coiling in 26 aneurysms, stent in one patient, and follow-up in the remaining 5 aneurysms. Dual-energy CTA correctly predicted treatment choice in 44 aneurysms, with 15 aneurysms coiled and 29 aneurysms clipped. Compared with DSA, DE-CTA had a comparable diagnostic accuracy for the detection of intracranial aneurysms, visualization of the morphology of aneurysms at the skull base, and prediction of aneurysm treatment choice in most patients with spontaneous subarachnoid hemorrhage based on this study.

Interobserver variability in the detection of cerebral venous thrombosis using CT venography with matched mask bone elimination

Objectives Computed tomography venography (CTV) has proven to be a reliable imaging method in the evaluation of cerebral venous thrombosis with good correlation to magnetic resonance (MR) imaging and digital subtraction angiography (DSA). It is fast and widely accessible, especially in the emergency setting. For better visualization of vascular structures bone is often removed from the images. The purpose of this study was to evaluate the quality of a fully automatic bone removal method, matched mask bone elimination (MMBE), and to assess the interobserver variability of the CTV technique. Patients and methods Fifty patients with clinical suspicion of cerebral venous thrombosis underwent multislice CTV with MMBE post-processing. Axial source images and maximum intensity projections were retrospectively evaluated by two neuroradiologists for quality of bone removal and for the presence or absence of thrombosis in nine dural sinuses and five deep cerebral veins. A per sinus/vein and a per patient analysis (thrombosis in at least one sinus or vein) was performed and interobserver agreement was assessed. Results Both observers considered bone removal good in all patients (100%). Interobserver agreement per patient was excellent ( κ = 0.83), with a full agreement in 47 of 50 patients (94%). The interobserver agreement per sinus or vein was good ( κ = 0.76), with a full agreement in 679 of 700 sinuses or veins (97%). Conclusion CTV aided with MMBE is a robust technique for visualization of the intracranial venous circulation, removing bone effectively. CTV has high interobserver agreement for presence or absence of cerebral venous thrombosis.

Carotid Computed Tomography Angiography With Automated Bone Suppression

Computed tomography angiography (CTA) is a well-accepted imaging modality to evaluate the vessels of the head and neck. To improve the assessment of vessels at or within the skull base, different techniques to suppress bone in the final CTA image have been developed. We sought to compare the performance of fully automated bone removal based on dual energy (DE) and image registration (bone subtraction CTA [BSCTA]) for the supraaortic vasculature. Twenty-seven patients underwent carotid CTA on a dual source CT system. Two scans were performed, one before and one after contrast agent injection in DE mode (simultaneous acquisition of 80 and 140 kV scans). For each patient, data sets were reconstructed for post processing with DE and BSCTA. Two examiners evaluated overall bone suppression and image quality regarding integrity of the vessel lumen of different vessel segments (n = 19) with a 5-point scale (1 = poor, 5 = excellent), CTA source data served as the reference. Wilcoxon signed rank test was used to determine differences between the techniques. Cohen's kappa was used to determine interobserver agreement. Both bone suppression techniques could be applied successfully in 25 patients with high overall image quality. Two patients were excluded from the evaluation for technical reasons. Interobserver agreement was excellent (kappa = 0.85). Mean score of all vessel segments for overall bone removal was 4.45 +/- 0.76 for DE and 4.33 +/- 1.02 for BSCTA; DE performed better in the vessel segment of the neck (external carotid artery, common carotid artery, V1 to V3 segment of the vertebral artery, subclavian artery), whereas BSCTA was superior in the cranial vessels (C3-C6 segment of the internal carotid artery, ophthalmic artery). Vessel integrity was superior with BSCTA, the mean score of all vessel segments for overall vessel integrity was 3.97 +/- 1.47 for DE and 4.49 +/- 0.98 for BSCTA, the subclavian artery was most frequently truncated using DE post processing (mean score: 1.44 +/- 1.2). Both techniques provided bone suppression in a fully automated way. DE provided more complete bone suppression in the neck, but at the cost of inferior vessel integrity, especially at the thoracic inlet. BSCTA showed excellent results for vessel integrity and was superior to DE in most of the vessels in or at the skull base.

Cervical and Cranial Computed Tomographic Angiography With Automated Bone Removal

In supraaortic vessels, bone subtracted maximum intensity projections make the evaluation of computed tomographic angiography (CTA) datasets easier and faster. Dual energy CT can be used for bone removal without user interaction. The purpose of this study was to compare the results of conventional and dual energy-based bone removal. Dual energy CT angiography of the supraaortic vessels was acquired in 30 patients at 140 and 80 kVp tube potential simultaneously. Thick images of 0.75 mm were reconstructed from both datasets, and an additional weighted average dataset using information from both tubes was calculated. Two readers independently assessed vessel delineation, completeness of bone removal, and vessel preservation, as well as adequacy for diagnostic evaluation after dual energy-based bone removal (DEBR) and conventional bone removal (CoBR). The Student t test and Wilcoxon rank sum test were applied to test differences between data for significance. Cohen's kappa-test was used to calculate the interobserver agreement. Of dual energy datasets DEBR 88.3% were rated as adequate for diagnostic evaluation compared with only 6.7% with CoBR, P < 0.001. Of DEBR (35%) contained all vessels and no bony structures, whereas all diagnostic CoBR still contained residual bone and showed partial vessel truncations. Vessel delineation was rated significantly better with DEBR. DEBR profited from stronger vascular enhancement, whereas it had no significant influence on CoBR. Reading times were 173 +/- 55 seconds with DEBR and 253 +/- 12 seconds with CoBR, P < 0.001, which corresponds to a reduction of 32%. Comparison of dual energy CTA versus single energy CTA showed a dose reduction of 29.0% to 43.7%. Dual Energy-based bone removal can remove bony structures from supraaortic CTA datasets without time-consuming user interaction. This leads to a significant reduction of reading time, radiation dose and improved vessel delineation.

3D visualization of intracranial structures- DSA software for CT data with automatic bone removal

3D visualization of intracranial structures- DSA software for CT data with automatic bone removal

Evaluation of neuro bone removal algorithms for CT angiography

Currently, radiologists use several techniques to evaluate and explore vessels inside the cranium of a neuro CT Angiography scan. Surrounding bone makes it difficult to accurately view the vessels that are close to the cranium and skull base. Manual sculpting and region growing techniques are available, but radiologists are interested in faster and more accurate techniques. Advances in bone removal using a non-contrast and contrast enhanced scan for automated bone removal yield promising results in this area. Two of these algorithms, Matched Mask Bone Elimination (MMBE) and Multi-Resolution Registration Bone Subtraction (MRBS), were tested on five patients in order to study which method resulted in better images. After evaluating each case based on five criteria, it was determined that although Matched Mask Bone Elimination had a better average score, its results were not statistically different from results obtain with the Multi-Resolution Registration Bone Subtraction technique.