71 resultados para 3D Sequential Imaging
Resumo:
Diseases of paranasal sinuses and nasal passages in horses can be a diagnostic challenge because of the complex anatomy of the head and limitations of many diagnostic modalities. Our hypothesis was that magnetic resonance (MR) imaging would provide excellent anatomical detail and soft tissue resolution, and would be accurate in the diagnosis of diseases of the paranasal sinuses and nasal passages in horses. Fourteen horses were imaged. Inclusion criteria were lesions located to the sinuses or nasal passages that underwent MR imaging and subsequent surgical intervention and/or histopathologic examination. A low field, 0.3 tesla open magnet was used. Sequences in the standard protocol were fast spin echo T2 sagittal and transverse, spin echo T1 transverse, short-tau inversion recovery (STIR) dorsal, gradient echo 3D T1 MPR dorsal (plain and contrast enhanced), spin echo T1 fatsat (contrast enhanced). Mean scan time to complete the examination was 53 min (range 39-99 min). Lesions identified were primary or secondary sinusitis (six horses), paranasal sinus cyst (four horses), progressive ethmoid hematoma (two horses), and neoplasia (two horses). The most useful sequences were fast spin echo T2 transverse and sagittal, STIR dorsal and FE3D MPR (survey and contrast enhanced). Fluid accumulation, mucosal thickening, presence of encapsulated contents, bone deformation, and thickening were common findings observed in MR imaging. In selected horses, magnetic resonance imaging is a useful tool in diagnosing lesions of the paranasal sinuses and nasal passages.
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Accurate three-dimensional (3D) models of lumbar vertebrae are required for image-based 3D kinematics analysis. MRI or CT datasets are frequently used to derive 3D models but have the disadvantages that they are expensive, time-consuming or involving ionizing radiation (e.g., CT acquisition). In this chapter, we present an alternative technique that can reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model. Cadaveric studies are conducted to verify the reconstruction accuracy by comparing the surface models reconstructed from a single lateral fluoroscopic image to the ground truth data from 3D CT segmentation. A mean reconstruction error between 0.7 and 1.4 mm was found.
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This paper proposed an automated 3D lumbar intervertebral disc (IVD) segmentation strategy from MRI data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based approach. After that, a three-dimensional (3D) variable-radius soft tube model of the lumbar spine column is built to guide the 3D disc segmentation. The disc segmentation is achieved as a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.
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This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.
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Until today, most of the documentation of forensic relevant medical findings is limited to traditional 2D photography, 2D conventional radiographs, sketches and verbal description. There are still some limitations of the classic documentation in forensic science especially if a 3D documentation is necessary. The goal of this paper is to demonstrate new 3D real data based geo-metric technology approaches. This paper present approaches to a 3D geo-metric documentation of injuries on the body surface and internal injuries in the living and deceased cases. Using modern imaging methods such as photogrammetry, optical surface and radiological CT/MRI scanning in combination it could be demonstrated that a real, full 3D data based individual documentation of the body surface and internal structures is possible in a non-invasive and non-destructive manner. Using the data merging/fusing and animation possibilities, it is possible to answer reconstructive questions of the dynamic development of patterned injuries (morphologic imprints) and to evaluate the possibility, that they are matchable or linkable to suspected injury-causing instruments. For the first time, to our knowledge, the method of optical and radiological 3D scanning was used to document the forensic relevant injuries of human body in combination with vehicle damages. By this complementary documentation approach, individual forensic real data based analysis and animation were possible linking body injuries to vehicle deformations or damages. These data allow conclusions to be drawn for automobile accident research, optimization of vehicle safety (pedestrian and passenger) and for further development of crash dummies. Real 3D data based documentation opens a new horizon for scientific reconstruction and animation by bringing added value and a real quality improvement in forensic science.
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This paper proposed an automated three-dimensional (3D) lumbar intervertebral disc (IVD) segmentation strategy from Magnetic Resonance Imaging (MRI) data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based template matching approach. Based on the estimated two-dimensional (2D) geometrical parameters, a 3D variable-radius soft tube model of the lumbar spine column is built by model fitting to the 3D data volume. Taking the geometrical information from the 3D lumbar spine column as constraints and segmentation initialization, the disc segmentation is achieved by a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.
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INTRODUCTION Since the initial publication in 2000, Angiotensin II-infused mice have become one of the most popular models to study abdominal aortic aneurysm in a pre-clinical setting. We recently used phase contrast X-ray based computed tomography to demonstrate that these animals develop an apparent luminal dilatation and an intramural hematoma, both related to mural ruptures in the tunica media in the vicinity of suprarenal side branches. AIMS The aim of this narrative review was to provide an extensive overview of small animal applicable techniques that have provided relevant insight into the pathogenesis and morphology of dissecting AAA in mice, and to relate findings from these techniques to each other and to our recent PCXTM-based results. Combining insights from recent and consolidated publications we aimed to enhance our understanding of dissecting AAA morphology and anatomy. RESULTS AND CONCLUSION We analyzed in vivo and ex vivo images of aortas obtained from macroscopic anatomy, histology, high-frequency ultrasound, contrast-enhanced micro-CT, micro-MRI and PCXTM. We demonstrate how in almost all publications the aorta has been subdivided into a part in which an intact lumen lies adjacent to a remodeled wall/hematoma, and a part in which elastic lamellae are ruptured and the lumen appears to be dilated. We show how the novel paradigm fits within the existing one, and how 3D images can explain and connect previously published 2D structures. We conclude that PCXTM-based findings are in line with previous results, and all evidence points towards the fact that dissecting AAAs in Angiotensin II-infused mice are actually caused by ruptures of the tunica media in the immediate vicinity of small side branches.
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This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.
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OBJECTIVE The aim of this study was to compare quantitative and semiquantitative parameters (signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], image quality, diagnostic confidence) from a standard brain magnetic resonance imaging examination encompassing common neurological disorders such as demyelinating disease, gliomas, cerebrovascular disease, and epilepsy, with comparable sequence protocols and acquisition times at 3 T and at 7 T. MATERIALS AND METHODS Ten healthy volunteers and 4 subgroups of 40 patients in total underwent comparable magnetic resonance protocols with standard diffusion-weighted imaging, 2D and 3D turbo spin echo, 2D and 3D gradient echo and susceptibility-weighted imaging of the brain (10 sequences) at 3 T and 7 T. The subgroups comprised patients with either lesional (n = 5) or nonlesional (n = 4) epilepsy, intracerebral tumors (n = 11), demyelinating disease (n = 11) (relapsing-remitting multiple sclerosis [MS, n = 9], secondary progressive MS [n = 1], demyelinating disease not further specified [n = 1]), or chronic cerebrovascular disorders [n = 9]). For quantitative analysis, SNR and CNR were determined. For a semiquantitative assessment of the diagnostic confidence, a 10-point scale diagnostic confidence score (DCS) was applied. Two experienced radiologists with additional qualification in neuroradiology independently assessed, blinded to the field strength, 3 pathology-specific imaging criteria in each of the 4 disease groups and rated their diagnostic confidence. The overall image quality was semiquantitatively assessed using a 4-point scale taking into account whether diagnostic decision making was hampered by artifacts or not. RESULTS Without correction for spatial resolution, SNR was higher at 3 T except in the T2 SPACE 3D, DWI single shot, and DIR SPACE 3D sequences. The SNR corrected by the ratio of 3 T/7 T voxel sizes was higher at 7 T than at 3 T in 10 of 11 sequences (all except for T1 MP2RAGE 3D).In CNR, there was a wide variation between sequences and patient cohorts, but average CNR values were broadly similar at 3 T and 7 T.DCS values for all 4 pathologic entities were higher at 7 T than at 3 T. The DCS was significantly higher at 7 T for diagnosis and exclusion of cortical lesions in vascular disease. A tendency to higher DCS at 7 T for cortical lesions in MS was observed, and for the depiction of a central vein and iron deposits within MS lesions. Despite motion artifacts, DCS values were higher at 7 T for the diagnosis and exclusion of hippocampal sclerosis in mesial temporal lobe epilepsy (improved detection of the hippocampal subunits). Interrater agreement was 69.7% at 3 T and 93.3% at 7 T. There was no significant difference in the overall image quality score between 3 T and 7 T taking into account whether diagnostic decision making was hampered by artifacts or not. CONCLUSIONS Ultra-high-field magnetic resonance imaging at 7 T compared with 3 T yielded an improved diagnostic confidence in the most frequently encountered neurologic disorders. Higher spatial resolution and contrast were identified as the main contributory factors.
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BACKGROUND Contrast-enhanced (ce) fluid-attenuated inversion recovery magnetic resonance imaging (FLAIR MRI) has recently been shown to identify leptomeningeal pathology in multiple sclerosis. OBJECTIVE To demonstrate leptomeningeal enhancement on three-dimensional (3D) FLAIR in a case of Susac's syndrome. METHODS Leptomeningeal enhancement was correlated with clinical activity over 20 months and compared to retinal fluorescein angiography. RESULTS The size, number, and location of leptomeningeal enhancement varied over time and generally correlated with symptom severity. The appearance was remarkably similar to that of retinal vasculopathy. CONCLUSION Ce 3D FLAIR may aid in diagnosis and understanding of pathophysiology in Susac's syndrome and may serve as a biomarker for disease activity.