6 resultados para 3D imaging

em Deakin Research Online - Australia


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Biofunctional nanorods are developed to specifically target cancer cells. The cervical cancer cells, HeLa cells, are labeled by these biofunctional gold nanorods. Those cancer cells can be detected by a multi-photon-excited photoluminescence endomicroscope, which proves that the cancers can be in vivo diagnosed by using biofunctional gold nanorods with nonlinear endomicroscopy.

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Despite Wheatstone’s academic interests in the device, the stereoscope languished somewhat as an optical toy. Yet the advent of 3D screen-spaces for home and mass entertainment suggests today’s consumers and practitioners of screen culture hold the view that screen culture will be ‘improved’ through 3D imaging technologies. Like cinema and photography, stereoscopic 3D imaging has the potential to transform visual culture. But what is transformed, as optics and electronic imaging techniques deliver Alice in Wonderland in 3D? This paper links the advent of 3D cinema and TV to the notion that vision is itself a ‘technology of the visual’. As such, our innate binocular stereoacuity is ripe for exploitation by developers of 3D imaging technologies. I argue that contemporary 3D imaging marks an epistemological visual-perceptual shift: toward screenspaces becoming spaces for potential action. Such a shift entails seeing as doing rather than seeing as thinking. 3D imaging exploits binocular vision’s spatial acuity (stereopsis), but is effective only for objects within near distal space. The 3D effect tapers off dramatically for objects only some metres away, because the two retinal images lack significant lateral disparity (difference) to trigger stereopsis: the imagery flattens out and becomes ‘monoscopic’. Information available from conventional 2D media entails a peculiarly unspecified spatiality. Perceptually, the contents of a conventional cinematic screen are like those of a painting: they are situated neither near nor far, and constitute a shared and ambiguous visual space. Our own eyes are like those of a cat: frontally placed for predatory action. The visuality of 3D screen-spaces assumes a perceptuality of the near-by and close at hand, since this is the structure of the visible information to which stereopsis is adapted to respond. Noting the binocular acuity of predatory animals, as well as some etymological links, this paper examines the implications of perceptually ‘capturing’ the sensation of visually solid objects in one’s immediate space. Stereopsis is about decisive action within an immediate environment: but it also presupposes the single viewpoint of an active observer toward which the 3D imagery is targeted.

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The ability to image electrochemical processes in situ using nuclear magnetic resonance imaging (MRI) offers exciting possibilities for understanding and optimizing materials in batteries, fuel cells and supercapacitors. In these applications, however, the quality of the MRI measurement is inherently limited by the presence of conductive elements in the cell or device. To overcome related difficulties, optimal methodologies have to be employed. We show that time-efficient three dimensional (3D) imaging of liquid and solid lithium battery components can be performed by Sectoral Fast Spin Echo and Single Point Imaging with T1 Enhancement (SPRITE), respectively. The former method is based on the generalized phase encoding concept employed in clinical MRI, which we have adapted and optimized for materials science and electrochemistry applications. Hard radio frequency pulses, short echo spacing and centrically ordered sectoral phase encoding ensure accurate and time-efficient full volume imaging. Mapping of density, diffusivity and relaxation time constants in metal-containing liquid electrolytes is demonstrated. 1, 2 and 3D SPRITE approaches show strong potential for rapid high resolution (7)Li MRI of lithium electrode components.

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A complete and highly robust 3D reconstruction algorithm based on stereo vision is presented. The developed system is capable of reconstructing dimensionally accurate 3D models of the objects and is very simple and cost effective due to its prominent software dependency and minimal hardware involvevment unlike existing systems.

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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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The evaluation of changes in Intervertebral Discs (IVDs) with 3D Magnetic Resonance (MR) Imaging (MRI) can be of interest for many clinical applications. This paper presents the evaluation of both IVD localization and IVD segmentation methods submitted to the Automatic 3D MRI IVD Localization and Segmentation challenge, held at the 2015 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2015) with an on-site competition. With the construction of a manually annotated reference data set composed of 25 3D T2-weighted MR images acquired from two different studies and the establishment of a standard validation framework, quantitative evaluation was performed to compare the results of methods submitted to the challenge. Experimental results show that overall the best localization method achieves a mean localization distance of 0.8 mm and the best segmentation method achieves a mean Dice of 91.8%, a mean average absolute distance of 1.1 mm and a mean Hausdorff distance of 4.3 mm, respectively. The strengths and drawbacks of each method are discussed, which provides insights into the performance of different IVD localization and segmentation methods.