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Impact of Matching Point Selections on Image Registration Accuracy between Optical Scan and Computed Tomography.

ABSTRACT: The point-based surface registration method involves the manual selection process of paired matching points on the data of computed tomography and optical scan. The purpose of this study was to investigate the impact of selection error and distribution of fiducial points on the accuracy of image matching between 3-dimensional (3D) images in dental planning software programs. Computed tomography and optical scan images of a partial edentulous dental arch were obtained. Image registration of the optical scan image to computed tomography was performed using the point-based surface registration method in planning software programs under different conditions of 3 fiducial points: point selection error (0, 1, or 2?mm), point distribution (unilateral, bilateral), and planning software (Implant Studio, Blue Bio Plan) (n = 5 per condition, N = 60). The accuracy of image registration at each condition was evaluated by measuring linear discrepancies between matched images at X, Y, and Z axes. Kruskal-Wallis test, Mann-Whitney U test with Bonferroni correction, and 3-way analysis of variance were used to statistically analyse the measurement data (? = 0.05). No statistically significant difference was exhibited between the 0 and 1?mm point mismatch conditions in either unilateral or bilateral point distributions. The discrepancy values in the 2?mm mismatch condition were significantly different from the other mismatch conditions, especially in the unilateral point distribution (P < 0.05). Strong interactions among point selection error, distribution, and software programs on the image registration were found (P < 0.001). Minor matching point selection error did not influence the accuracy of point-based automatic image registration in the software programs. When the fiducial points are distributed unilaterally with large point selection error, the image matching accuracy could be decreased.

SUBMITTER: Mai HY

PROVIDER: S-EPMC7426779 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Impact of Matching Point Selections on Image Registration Accuracy between Optical Scan and Computed Tomography.

Mai Hai Yen HY Lee Du-Hyeong DH

BioMed research international 20200804

The point-based surface registration method involves the manual selection process of paired matching points on the data of computed tomography and optical scan. The purpose of this study was to investigate the impact of selection error and distribution of fiducial points on the accuracy of image matching between 3-dimensional (3D) images in dental planning software programs. Computed tomography and optical scan images of a partial edentulous dental arch were obtained. Image registration of the o ...[more]

PMID: 32802841

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Project description:ObjectivesComputed tomography angiography (CTA) is the imaging modality most frequently used to diagnosis type A aortic dissection for chest pain with a high degree of sensitivity and specificity. False negative and positive errors in diagnosis are infrequent. Despite initial negative imaging studies for dissection, surgeons must consider early operation in patients with recent onset chest pain in the presence of an ascending aortic aneurysm.MethodsWe report 4 cases (2004-2021) of patients with a mean age of 51.25 years (male:female = 3:1) who presented with chest pain. Two had a history of syncope. On computed tomography angiography, all had an ascending aortic aneurysm and no dissection flap. Three had thickening of the ascending aorta and 1 had a chronic type B dissection. On echocardiography, aortic regurgitation was moderate-severe in 2 patients, 2 had a pericardial effusion, and none had a definitive dissection flap. All were operated on because of the surgeon's concern for the association of chest pain and an ascending aortic aneurysm. The Institutional Review Board at George Washington University Committee on Human Research has determined that the research is exempt from review under Department of Health and Human Services regulatory category 4 (#FWA00005945). The project as described in the application may proceed without further oversight by the Office of Human Resources on September 9, 2022.ResultsThe diagnosis of type A aortic dissection was made at operation (3 on median sternotomy and 1 after aortotomy). All patients did well. One patient who had peripheral cannulation (no malperfusion) and severe coagulopathy developed a compartment syndrome and postoperatively required a below-knee amputation.ConclusionsSurgeons must maintain a high index of suspicion for aortic dissection when patients present with chest pain and are found to have an ascending aortic aneurysm even in the absence of initial, classic features of dissection on computed tomography angiography. Improvements in imaging techniques and analysis are required.

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Project description:OBJECTIVE:To compare the accuracy of different methods for image registration in image-guided adaptive brachytherapy (IGABT) for cervical cancer. METHODS:The last treatment planning CT images (CT1) and the first treatment planning CT images (CT2) were acquired from 15 patients with cervical cancer and registered with different match image qualities (retained/removed catheter source in images) and different match regions [target only (S Group)/ interested organ structure (M Group)/body (L Group)] in Velocity3.2 software. The dice similarity coefficient (DSC) between the clinical target volumes (CTV) of the CT1 and CT2 images (CTVCT1 and CTVCT2, respectively) and between the organs-at-risk (OAR) of the two imaging datasets (OARCT1 and OARCT2, respectively) were used to evaluate the image registration accuracy. RESULTS:The auto-segmentation volume of the catheter source using Velocity software based on the CT threshold was the closest to the actual volume within the CT value range of 1700-1800 HU. In the retained group, the DSC for the OARs of was better than or equal to that of the removed group, and the DSC value of the rectum was significantly improved (P < 0.05). For comparison of different match regions, the high-risk target volume (HRCTV) and the low-risk target volume (IRCTV) had the best precision for registration of the target area, which was significantly greater than that of M group and L group (P < 0.05). The M group had better registration accuracy of the target area and the best accuracy for the OARs. The DSC values of the bladder and rectum were significantly better than those of the other two groups (P < 0.05). CONCLUSIONS:The CT value range of 1700-1800 HU is optimal for automatic image segmentation using Velocity software. Automatic segmentation and shielding the volume of the catheter source can improve the image quality. We recommend the use of interested organ structures regions for image registration in image-guided adaptive brachytherapy for cervical cancer.

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Impact of Matching Point Selections on Image Registration Accuracy between Optical Scan and Computed Tomography.

Publications

Impact of Matching Point Selections on Image Registration Accuracy between Optical Scan and Computed Tomography.

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