36 resultados para distinctness of image
em BORIS: Bern Open Repository and Information System - Berna - Suiça
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The standard of care for locally advanced anal cancer has been concurrent chemoradiation. However, conventional treatment with 3-dimensional radiotherapy is associated with significant toxicity. The feasibility of new radiotherapy techniques such as image-guided radiotherapy (IGRT) in combination with chemotherapy for the treatment of this malignancy was assessed.
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Image-guided microsurgery requires accuracies an order of magnitude higher than today's navigation systems provide. A critical step toward the achievement of such low-error requirements is a highly accurate and verified patient-to-image registration. With the aim of reducing target registration error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled localization of fiducials on the patient is achieved through the implementation of a robotic-controlled tactile search within the head of a standard surgical screw. Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high-resolution, isometric cone beam CT images. Verification of the registration technique on phantoms demonstrated that through the elimination of user variability, clinically relevant target registration errors of approximately 0.1 mm could be achieved.
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BackgroundDespite the increasingly higher spatial and contrast resolution of CT, nodular lesions are prone to be missed on chest CT. Tinted lenses increase visual acuity and contrast sensitivity by filtering short wavelength light of solar and artificial origin.PurposeTo test the impact of Gunnar eyewear, image quality (standard versus low dose CT) and nodule location on detectability of lung nodules in CT and to compare their individual influence.Material and MethodsA pre-existing database of CT images of patients with lung nodules >5 mm, scanned with standard does image quality (150 ref mAs/120 kVp) and lower dose/quality (40 ref mAs/120 kVp), was used. Five radiologists read 60 chest CTs twice: once with Gunnar glasses and once without glasses with a 1 month break between. At both read-outs the cases were shown at lower dose or standard dose level to quantify the influence of both variables (eyewear vs. image quality) on nodule sensitivity.ResultsThe sensitivity of CT for lung nodules increased significantly using Gunnar eyewear for two readers and insignificantly for two other readers. Over all, the mean sensitivity of all radiologist raised significantly from 50% to 53%, using the glasses (P value = 0.034). In contrast, sensitivity for lung nodules was not significantly affected by lowering the image quality from 150 to 40 ref mAs. The average sensitivity was 52% at low dose level, that was even 0.7% higher than at standard dose level (P value = 0.40). The strongest impact on sensitivity had the factors readers and nodule location (lung segments).ConclusionSensitivity for lung nodules was significantly enhanced by Gunnar eyewear (+3%), while lower image quality (40 ref mAs) had no impact on nodule sensitivity. Not using the glasses had a bigger impact on sensitivity than lowering the image quality.
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In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.
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OBJECTIVE: To compare image quality and radiation dose of thoracoabdominal computed tomography (CT) angiography at 80 and 100 kVp and to assess the feasibility of reducing contrast medium volume from 60 to 45 mL at 80 kVp. MATERIALS AND METHODS: This retrospective study had institutional review board approval; informed consent was waived. Seventy-five patients who had undergone thoracoabdominal 64-section multidetector-row CT angiography were divided into 3 groups of 25 patients each. Patients of groups A (tube voltage, 100 kVp) and B (tube voltage, 80 kVp) received 60 mL of contrast medium at 4 mL/s. Patients of group C (tube voltage, 80 kVp) received 45 mL of contrast medium at 3 mL/s. Mean aortoiliac attenuation, image noise, and contrast-to-noise ratio were assessed. The measurement of radiation dose was based on the volume CT dose index. Three independent readers assessed the diagnostic image quality. RESULTS: Mean aortoiliac attenuation for group B (621.1 +/- 90.5 HU) was significantly greater than for groups A and C (485.2 +/- 110.5 HU and 483.1 +/- 119.8 HU; respectively) (P < 0.001). Mean image noise was significantly higher for groups B and C than for group A (P < 0.05). The contrast-to-noise ratio did not significantly differ between the groups (group A, 35.0 +/- 13.8; group B, 31.7 +/- 10.1; group C, 27.3 +/- 11.5; P = 0.08). Mean volume CT dose index in groups B and C (5.2 +/- 0.4 mGy and 4.9 +/- 0.3 mGy, respectively) were reduced by 23.5% and 27.9%, respectively, compared with group A (6.8 +/- 0.8 mGy) (P < 0.001). The average overall diagnostic image quality for the 3 groups was graded as good or better. The score for group A was significantly higher than that for group C (P < 0.01), no difference was seen between group A and B (P = 0.92). CONCLUSIONS: Reduction of tube voltage from 100 to 80 kVp for thoracoabdominal CT angiography significantly reduces radiation dose without compromising image quality. Reduction of contrast medium volume to 45 mL at 80 kVp resulted in lower but still diagnostically acceptable image quality.
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HYPOTHESIS A previously developed image-guided robot system can safely drill a tunnel from the lateral mastoid surface, through the facial recess, to the middle ear, as a viable alternative to conventional mastoidectomy for cochlear electrode insertion. BACKGROUND Direct cochlear access (DCA) provides a minimally invasive tunnel from the lateral surface of the mastoid through the facial recess to the middle ear for cochlear electrode insertion. A safe and effective tunnel drilled through the narrow facial recess requires a highly accurate image-guided surgical system. Previous attempts have relied on patient-specific templates and robotic systems to guide drilling tools. In this study, we report on improvements made to an image-guided surgical robot system developed specifically for this purpose and the resulting accuracy achieved in vitro. MATERIALS AND METHODS The proposed image-guided robotic DCA procedure was carried out bilaterally on 4 whole head cadaver specimens. Specimens were implanted with titanium fiducial markers and imaged with cone-beam CT. A preoperative plan was created using a custom software package wherein relevant anatomical structures of the facial recess were segmented, and a drill trajectory targeting the round window was defined. Patient-to-image registration was performed with the custom robot system to reference the preoperative plan, and the DCA tunnel was drilled in 3 stages with progressively longer drill bits. The position of the drilled tunnel was defined as a line fitted to a point cloud of the segmented tunnel using principle component analysis (PCA function in MatLab). The accuracy of the DCA was then assessed by coregistering preoperative and postoperative image data and measuring the deviation of the drilled tunnel from the plan. The final step of electrode insertion was also performed through the DCA tunnel after manual removal of the promontory through the external auditory canal. RESULTS Drilling error was defined as the lateral deviation of the tool in the plane perpendicular to the drill axis (excluding depth error). Errors of 0.08 ± 0.05 mm and 0.15 ± 0.08 mm were measured on the lateral mastoid surface and at the target on the round window, respectively (n =8). Full electrode insertion was possible for 7 cases. In 1 case, the electrode was partially inserted with 1 contact pair external to the cochlea. CONCLUSION The purpose-built robot system was able to perform a safe and reliable DCA for cochlear implantation. The workflow implemented in this study mimics the envisioned clinical procedure showing the feasibility of future clinical implementation.
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We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.
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In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.
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The combined use of androgen deprivation therapy (ADT) and image-guided radiotherapy (IGRT) can improve overall survival in aggressive, localized prostate cancer. However, owing to the adverse effects of prolonged ADT, it is imperative to identify the patients who would benefit from this combined-modality therapy relative to the use of IGRT alone. Opportunities exist for more personalized approaches in treating aggressive, locally advanced prostate cancer. Biomarkers--such as disseminated tumour cells, circulating tumour cells, genomic signatures and molecular imaging techniques--could identify the patients who are at greatest risk for systemic metastases and who would benefit from the addition of systemic ADT. By contrast, when biomarkers of systemic disease are not present, treatment could proceed using local IGRT alone. The choice of drug, treatment duration and timing of ADT relative to IGRT could be predicated on these personalized approaches to prostate cancer medicine. These novel treatment intensification and reduction strategies could result in improved prostate-cancer-specific survival and overall survival, without incurring the added expense of metabolic syndrome and other adverse effects of ADT in all patients.
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To assess the temperature dependency of tissue contrast on post mortem magnetic resonance (PMMR) images both objectively and subjectively; and to visually demonstrate the changes of image contrast at various temperatures.
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OBJECTIVE: Measures to reduce radiation exposure and injected iodine mass are becoming more important with the widespread and often repetitive use of pulmonary CT angiography (CTA) in patients with suspected pulmonary embolism. In this retrospective study, we analyzed the capability of 2 low-kilovoltage CTA-protocols to achieve these goals. MATERIALS AND METHODS: Ninety patients weighing less than 100 kg were examined by a pulmonary CTA protocol using either 100 kVp (group A) or 80 kVp (group B). Volume and flow rate of contrast medium were reduced in group B (75 mL at 3 mL/s) compared with group A (100 mL at 4 mL/s). Attenuation was measured in the central and peripheral pulmonary arteries, and the contrast-to-noise ratios (CNR) were calculated. Entrance skin dose was estimated by measuring the surface dose in an ovoid-cylindrical polymethyl methacrylate chest phantom with 2 various dimensions corresponding to the range of chest diameters in our patients. Quantitative image parameters, estimated effective dose, and skin dose in both groups were compared by the t test. Arterial enhancement, noise, and overall quality were independently assessed by 3 radiologists, and results were compared between the groups using nonparametric tests. RESULTS: Mean attenuation in the pulmonary arteries in group B (427.6 +/- 116 HU) was significantly higher than in group A (342.1 +/- 87.7 HU; P < 0.001), whereas CNR showed no difference (group A, 20.6 +/- 7.3 and group B, 22.2 +/- 7.1; P = 0.302). Effective dose was lower by more than 40% with 80 kVp (1.68 +/- 0.23 mSv) compared with 100 kVp (2.87 +/- 0.88 mSv) (P < 0.001). Surface dose was significantly lower at 80 kVp compared with 100 kVp at both phantom dimensions (2.75 vs. 3.22 mGy; P = 0.027 and 2.22 vs. 2.73 mGy; P = 0.005, respectively). Image quality did not differ significantly between the groups (P = 0.151). CONCLUSIONS: Using 80 kVp in pulmonary CTA permits reduced patient exposure by 40% and CM volume by 25% compared with 100 kVp without deterioration of image quality in patients weighing less than 100 kg.
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Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.
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Coronary late stent thrombosis, a rare but devastating complication, remains an important concern in particular with the increasing use of drug-eluting stents. Notably, pathological studies have indicated that the proportion of uncovered coronary stent struts represents the best morphometric predictor of late stent thrombosis. Intracoronary optical frequency domain imaging (OFDI), a novel second-generation optical coherence tomography (OCT)-derived imaging method, may allow rapid imaging for the detection of coronary stent strut coverage with a markedly higher precision when compared with intravascular ultrasound, due to a microscopic resolution (axial approximately 10-20 microm), and at a substantially increased speed of image acquisition when compared with first-generation time-domain OCT. However, a histological validation of coronary OFDI for the evaluation of stent strut coverage in vivo is urgently needed. Hence, the present study was designed to evaluate the capacity of coronary OFDI by electron (SEM) and light microscopy (LM) analysis to detect and evaluate stent strut coverage in a porcine model.