20,575 research outputs found
Holographic microscopy reconstruction in both object and image half spaces with undistorted 3D grid
We propose an holographic microscopy reconstruction method, which propagates
the hologram, in the object half space, in the vicinity of the object. The
calibration yields reconstructions with an undistorted reconstruction grid i.e.
with orthogonal , and axis and constant pixels pitch. The method is
validated with an USAF target imaged by a 60 microscope objective,
whose holograms are recorded and reconstructed for different USAF locations
along the longitudinal axis: -75 to +75 m. Since the reconstruction
numerical phase mask, the reference phase curvature and MO form an afocal
device, the reconstruction can be interpreted as occurring equivalently in the
object or in image half space
Tracking of secondary and temporary objects in structural concrete work
Previous research has shown that “Scan-vs-BIM ” object recognition systems, that fuse 3D point clouds from Terrestrial Laser Scanning (TLS) or digital photogrammetry with 4D project BIM, provide valuable information for tracking structural works. However, until now, the potential of these systems has been demonstrated for tracking progress of permanent structures only; no work has been reported yet on tracking secondary or temporary structures. For structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. Together, they constitute most of the earned value in concrete work. The impact of tracking such elements would thus be added veracity and detail to earned value calculations, and subsequently better project control and performance. This paper presents three different techniques for recognizing concrete construction secondary and temporary objects in TLS point clouds. Two of the techniques are tested using real-life data collected from a reinforced concrete building construction site. The preliminary experimental results show that it is feasible to recognize secondary and temporary objects in TLS point clouds with good accuracy; but it is envisaged that superior results could be achieved by using additional cues such colour and 3D edge information
Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing
We have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionaly, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers
Ultrasound (US) is the most widely used fetal imaging technique. However, US
images have limited capture range, and suffer from view dependent artefacts
such as acoustic shadows. Compounding of overlapping 3D US acquisitions into a
high-resolution volume can extend the field of view and remove image artefacts,
which is useful for retrospective analysis including population based studies.
However, such volume reconstructions require information about relative
transformations between probe positions from which the individual volumes were
acquired. In prenatal US scans, the fetus can move independently from the
mother, making external trackers such as electromagnetic or optical tracking
unable to track the motion between probe position and the moving fetus. We
provide a novel methodology for image-based tracking and volume reconstruction
by combining recent advances in deep learning and simultaneous localisation and
mapping (SLAM). Tracking semantics are established through the use of a
Residual 3D U-Net and the output is fed to the SLAM algorithm. As a proof of
concept, experiments are conducted on US volumes taken from a whole body fetal
phantom, and from the heads of real fetuses. For the fetal head segmentation,
we also introduce a novel weak annotation approach to minimise the required
manual effort for ground truth annotation. We evaluate our method
qualitatively, and quantitatively with respect to tissue discrimination
accuracy and tracking robustness.Comment: MICCAI Workshop on Perinatal, Preterm and Paediatric Image analysis
(PIPPI), 201
A Survey of "The Sala degli Stucchi, an ornate baroque hall"
The "Sala degli stucchi" is a heavely decorated baroque hall, as the Italian name itself suggests, in the Royal Palace in Turin. The present work describes a survey of this historic object. This work is a part of a wider project on the study of Architectural Patrimony carried out for the La Soprintendenza per il Patrimonio storico, artistico ed etnoantropologico per il Piemonte. It is a chance to test the modern survey techniques of photogrammetry and LIDAR. This article focuses on the integrated use of digital photogrammetry and LIDAR in a demanding environment, in order to take best advantages of both techniques. Different survey products were obtained, ranging from 3D and photogrammetric models to orthophotos. The adopted techniques, the problems and difficulties that arose during the survey process are shown in the paper. The obtained and stored results were also used to make a complete 3D model of the whole hal
Terrestrial laser scanning and 3D imaging: Heritage case study – The Black Gate, Newcastle Upon Tyne
This paper offers a case study on the recording of a section of wall on a complex heritage building, the Black Gate in Newcastle upon Tyne. The paper adopts case study methodology to assess the appropriateness of using a long range scanner based upon pulse technology for the recording of part of this historic structure and describes the scanning instruments adopted as well as the selection of appropriate software for the pre-processing and documentation. The study offers an overview of the survey planning stages, field operation, and processing of 3D point cloud data using the third party software adopted, including problems encountered. Issues emerging are discussed, in both the 2D and 3D modelling of detailed surfaces from point cloud data, and in the process of software selection, data preparation and export, pre-processing of point cloud data, meshing and the creation of 2D geometry and 3D animations. The paper describes the end results offered as deliverables for this project, and offers recommendations for a working method that can produce data suitable for producing stone-by-stone elevation drawings. The work processes and cost / time indicators are included in this case study and conclusions will consider whether the technique adopted could lead to an improved solution for heritage recording compared to those traditional techniques which are currently employed to produce stone-by-stone elevations. Areas for future research are identified
From 3D Models to 3D Prints: an Overview of the Processing Pipeline
Due to the wide diffusion of 3D printing technologies, geometric algorithms
for Additive Manufacturing are being invented at an impressive speed. Each
single step, in particular along the Process Planning pipeline, can now count
on dozens of methods that prepare the 3D model for fabrication, while analysing
and optimizing geometry and machine instructions for various objectives. This
report provides a classification of this huge state of the art, and elicits the
relation between each single algorithm and a list of desirable objectives
during Process Planning. The objectives themselves are listed and discussed,
along with possible needs for tradeoffs. Additive Manufacturing technologies
are broadly categorized to explicitly relate classes of devices and supported
features. Finally, this report offers an analysis of the state of the art while
discussing open and challenging problems from both an academic and an
industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and
Innovation action; Grant agreement N. 68044
A Survey on Deep Learning in Medical Image Analysis
Deep learning algorithms, in particular convolutional networks, have rapidly
become a methodology of choice for analyzing medical images. This paper reviews
the major deep learning concepts pertinent to medical image analysis and
summarizes over 300 contributions to the field, most of which appeared in the
last year. We survey the use of deep learning for image classification, object
detection, segmentation, registration, and other tasks and provide concise
overviews of studies per application area. Open challenges and directions for
future research are discussed.Comment: Revised survey includes expanded discussion section and reworked
introductory section on common deep architectures. Added missed papers from
before Feb 1st 201
Wire mesh design
We present a computational approach for designing wire meshes, i.e., freeform surfaces composed of woven wires arranged in a regular grid. To facilitate shape exploration, we map material properties of wire meshes to the geometric model of Chebyshev nets. This abstraction is exploited to build an efficient optimization scheme. While the theory of Chebyshev nets suggests a highly constrained design space, we show that allowing controlled deviations from the underlying surface provides a rich shape space for design exploration. Our algorithm balances globally coupled material constraints with aesthetic and geometric design objectives that can be specified by the user in an interactive design session. In addition to sculptural art, wire meshes represent an innovative medium for industrial applications including composite materials and architectural façades. We demonstrate the effectiveness of our approach using a variety of digital and physical prototypes with a level of shape complexity unobtainable using previous methods
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