Comparison of two well-established 3d acquisition techniques on a

Metrics details. This requires hospitals and their personnel to update their quality assurance program to more appropriately accommodate the 3D printing fabrication process and the challenges that come along with it.

In this paper, we explored different methods for verifying the accuracy of a 3D printed anatomical model. Methods included physical measurements, digital photographic measurements, surface scanning, photogrammetry, and computed tomography CT scans. The details of each verification method, as well as their benefits and challenges, are discussed. There are multiple methods for model verification, each with benefits and drawbacks. The choice of which method to adopt into a quality assurance program is multifactorial and will depend on the type of 3D printed models being created, the training of personnel, and what resources are available within a 3D printed laboratory.

One of the most compelling use cases for 3D printing in medicine is the creation of patient-specific anatomical models for presurgical planning [ 123 ]. Due to positive feedback from the use of these 3D printed anatomical models during pre-surgical consultations, there has been a push to explore additional ways that 3D models can be used. Other examples of using 3D printed models in the hospital include benchtop surgical simulation [ 567 ], sizing of devices prior to a surgery or procedure [ 8910111213 ], and designing patient-matched surgical cutting guides [ 1415 ] or implants [ 161718192021 ].

Established quality assurance QA programs exist for many areas of medicine, including medical imaging. In radiology, these include Quality Control QC programs for ensuring optimal performance of imaging acquisition hardware [ 2223 ] and QA programs for dose reduction, appropriate use, radiologist interpretations, and reporting of results [ 24 ].

A handful of hospitals have led the way in adapting and extending imaging QA programs for use in 3D printing [ 252627 ], including the creation of new phantoms that test the performance and accuracy of 3D printers and materials [ 126 ]. As 3D printing programs push past enhanced visualization as a product deliverable and begin to create true medical devices, there is a need to expand the existing QA programs within hospitals to create a more robust QA program inclusive of 3D printing as a clinical resource.

Verification refers to ensuring that a part is physically made to product specifications within a given tolerance e. Verification that a part is built to pre-defined specifications may seem straightforward on the surface, but it can pose multiple challenges in the 3D printing space. These reference dimensions are often impossible to physically measure if the anatomy is internal, and therefore the reference standard for a given 3D model or part is often based on medical imaging, which becomes a stand-in for ground truth.

In this paper, we explore several measurement methods for verifying the accuracy of 3D-printed cardiac models and discuss some of the unique challenges we encountered with each method. This work is not meant to determine the superiority of one technique over the other nor to make a statement about what technique should ultimately be used. Instead, it is meant as an overview and a conversation starter concerning the challenges inherent in part verification.Optimal acquisition strategies for single-photon 3D cameras: Towards long-range laser-scan quality 3D imaging.

A conventional camera sensor needs hundreds of photon per pixel to form an image. A single-photon sensor, on the other hand, is so sensitive to incident light that it can capture individual photons with picosecond resolution time-tags. This high-resolution time dimension provides a rich source of information that is not available to conventional cameras. For example, this can enable long-range laser-scan quality 3D imaging. In this work we use an emerging single-photon sensor technology called a single-photon avalanche diode SPAD sensor.

Due to their peculiar image formation model, extreme ambient light incident on a SPAD-based 3D camera causes severe distortions photon pileup leading to large depth errors. We address the following basic question: What is the optimal acquisition scheme for a SPAD-based 3D camera that minimizes depth errors when operating in high ambient light?

In this line of work we present asynchronous acquisition schemes that mitigate pileup in data acquisition itself. Asynchronous acquisition involves temporally misaligning the SPAD measurements with respect to the laser, averaging out the effect of pileup.

comparison of two well-established 3d acquisition techniques on a

Additionally, we also propose optimal optical attenuation as a method for reducing pileup distortions while maintaining high SNR. Our simulations and experiments demonstrate an improvement in depth accuracy of up to an order of magnitude as compared to the state-of-the-art, across a wide range of imaging scenarios, including those with high ambient flux.

Histogram formation and effect of ambient light: A single-photon 3D camera forms a histogram of the first photon arrival times over many laser cycles. In case of no ambient light, the peak of this histogram corresponds to the true depth. However, in case of strong ambient light, the histogram gets distorted due to early-arriving ambient light photons and the true signal peak gets buried in the exponentially decaying tail. For an interactive tool explaining histogram formation, visit: tiny.

We propose a two acquisition strategies to deal with photon pileup. The first strategy involves optimally attenuating a fraction of the total light incident on the SPAD sensor. The second strategy of asynchronous acquisition involves temporally staggering the SPAD measurement windows with respect to the laser to average out the effect of photon pileup. When used in combination, these strategies enable us to mitigate photon pileup in acquisition itself and reliably estimate scene depths even in high ambient light.

You can find interactive tools here: tiny.

3D Vision Made Easy

Reconstructions for a castle scene: With insufficient attenuation, scene points closer to the camera are recovered correctly, but points farther away are lost due to ambient light.

With extreme attenuation, points at all depths are recovered albeit with poor accuracy.This is the term use for consolidation of businesses or their assets. This template of various slides with numerus process flow diagrams, data tables, logic and analysis charts.

comparison of two well-established 3d acquisition techniques on a

Further, the PowerPoint of Mergers and Acquisitions defines different terms related to the topic in each slide. Here, the big fish going after smaller fish is the metaphor for mergers, the presentation contains many illustrations.

Similarly, the visual presentation of acquisition is via hand shake and teamwork graphics. These graphic and diagram are editable to modify design according to presentation theme. Further topics given in slides include:.

Measuring crops in 3D: using geometry for plant phenotyping

Merger business model design 3. Merger Timeframe 4. Flow chart of acquisition 6. Capabilities and position asset analysis 7.

comparison of two well-established 3d acquisition techniques on a

Merger and acquisition integration 8. Post acquisition integration framework 9. Types of mergers Types of due diligence. These model concepts in Mergers and Acquisitions PowerPoint Template are helpful for any business value preposition. For instance, any industry professionals can choose the desire slide to add in the mergers and acquisitions presentation.

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Mergers and Acquisitions PowerPoint Template. Further topics given in slides include: 1. Types of due diligence These model concepts in Mergers and Acquisitions PowerPoint Template are helpful for any business value preposition. Item How to get this PowerPoint Template? Subscribe today and get immediate access to download our PowerPoint templates.

Subscribe Now. Spiral Diagram Concept for PowerPoint.Real-time three-dimensional 3D ultrasound US has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations.

Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional 2D probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed.

Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented.

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Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail. Each imaging modality has its strengths and limitations in different applications [ 1 ]. Among these diagnosis-aid technologies, US gains more and more attention in recent years. Aside from low cost and no radiation, the interactive nature of US which is mostly needed in surgery facilitates its widespread use in clinical practices.

Conventional 2D US has been widely used because it can dynamically display 2D images of the region of interest ROI in real-time [ 23 ]. However, due to the lack of the anatomy and orientation information, clinicians have to imagine the volume with the planar 2D images mentally when they need the view of 3D anatomic structures.

The limitation of 2D US imaging makes the diagnostic accuracy much uncertain as it heavily depends on the experience and knowledge of clinicians.

In order to address the foresaid problem, 3D US was proposed to help the diagnosticians acquire a full understanding of the spatial anatomic relationship. Physicians can view arbitrary plane of the reconstructed 3D volume as well as panoramic view of the ROI which helps surgeons to ascertain whether a surgical instrument is placed correctly within the ROI or just locates peripherally during the surgery [ 4 ].

It is undeniable that 3D US enables clinicians to diagnose fast and accurately as it reduces the time spent on evaluating images and interacts with diagnosticians friendly to obtain a handle of the shape and location of the lesion.

Generally, 3D US imaging can be conducted with three main stages: that is, acquisition, reconstruction, and visualization. The acquisition refers to collecting the B-scans with relative position using conventional 2D probes or directly obtaining 3D images using dedicated 3D probes.

The reconstruction aims to insert the collected 2D images into a predefined regular volume grid. The visualization is to render the built voxel array in a certain manner like any-plane slicing, surface rendering, or volume rendering. Traditional 3D US is temporally separated into the B-scan frame collection, volume reconstruction, and visualization stages individually, making it time-consuming and inefficient to obtain an accurate 3D image.

Clinician has to wait for the data collection and volume reconstruction which often take several minutes or even longer time before visualizing any part of the volume, rather than visualizing 3D anatomy simultaneously during the scanning of the ROI.

Hence the clinician cannot select an optimal way to conduct the scanning process for subsequent diagnosis. Moreover, the separation has limited the applications in surgery where physicians require immediate feedback on intraoperative changes in the ROI [ 5 ].

Many investigators have made their efforts to develop the real-time or near real-time US systems in recent decade. Several attempts with the dedicated 3D probe or traditional 2D probe to reconstruct and render a volume during data acquisition are now available.

To provide systematic understanding of the relevant technology in real-time US, we review the state-of-the-art approaches for designing real-time or near real-time 3D US imaging system. Data acquisition techniques, reconstruction algorithms, rendering methods, and clinical applications are discussed in the following sections, including the advantage and disadvantages of each approach. Obtaining 3D real-time US image without distortions is crucial for the subsequent clinical diagnosis.

In any approach of data acquisition, the objectives are twofold: first to acquire relative locations and orientations of the tomographic images accurately, which ensures the 3D reconstruction without errors, and second to capture the ROI expeditiously, which is aimed at avoiding the artifacts caused by cardiac, respiratory, and involuntary motion, as well as enabling the 3D visualization of dynamic structures in real-time.

Four representative real-time 3D US data acquisition techniques have been proposed, that is, 2D array transducers, mechanical 3D probes, mechanical localizers, and freehand scanners. In conventional 1D array transducer, a subset of transducer elements or subaperture is sequentially selected to send an acoustic beam perpendicularly to the transducer surface, and one line is drawn at the same time.

Through multiplexing or simply turning elements on and off, the entire aperture can be selected which forms a rectangular scan [ 6 ]. Analogously, 2D array transducers derive an acoustic beam steering in both azimuth and elevation dimensions, which enables obtaining a volumetric scan [ 7 ]. As illustrated in Figure 1the elements of 2D array transducer generate a diverging beam in a pyramidal shape and the received echoes are processed to integrate 3D US images in real-time.Traditional two-dimensional 2D cell culturing techniques have been accepted as economical and convenient in vitro analysing strategies to assess the characteristics of antibody-drug conjugates ADCs and other therapeutic agents.

With the methodology established over a century ago, traditional techniques grow cells in two dimensions, by attaching cells on a plastic substrate or suspending cells in a thin layer of liquid medium, resulting in monolayer cell cultures. Those monolayer cells are simple and ready-to-use models for the high throughput screening of newly developed ADCs.

In vitro analysis using 2D cell culture models provides primary indications of the targeting ability, internalization efficiency, and cytotoxicity of ADCs.

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However, failures of 2D-model-screened drugs in pre-clinical in vivo tests or clinical trials indicate that in vitro 2D cell cultures are not necessarily adequate models to precisely reveal the in vivo behaviours and dynamics of drugs. For the development of highly efficient therapeutic agents, anti-cancer ADCs as examples, the targeting ability, internalization efficiency, drug releasing capacity and payload cytotoxicity of ADCs, as well as their tissue penetration ability, distribution pattern and bystander killing efficiency should all be assessed and optimized.

However, in traditional 2D models with only a single layer of cells, it is not feasible to accurately evaluate the penetration, distribution or bystander killing patterns of ADCs.

Besides, cells in 2D cultures, due to the lack of cell-cell and cell-matrix interactions, grow and behave differently from those growing in vivo in three dimensions. Therefore, 2D cultured cells, upon the treatment by ADCs, may respond differently from the same type of cells in vivo.

Single-Photon 3D Imaging

These aspects limit the value of analysing results using 2D culture models, and promote the emerging of three-dimensional 3D cell culturing techniques. As it is possible to generate solid tumor spheroid or micro-tissue models via 3D culturing techniques, the tissue penetration and bystander killing efficiency of ADCs can be assessed using these in vitro models.

Simplified scheme comparing in vitro analysis of therapeutic agents using 2D and 3D models. With expertise and years of experiences in in vitro analysis, Creative Biolabs provides comprehensive analysis of ADCs using both 2D and 3D culture models.

The advanced 3D cell culture platform at Creative Biolabs enables the thorough assessment of ADCs, including their targeting ability, tumor penetration and internalization efficiency, as well as killing and bystander killing capacity. Through in-depth comparison between 2D and 3D analysing results, our science team at Creative Biolabs also provides customers with advices on the design and optimization of ADC products before in vivo tests.

This advanced 2D vs. Please contact us for more information and a detailed quote. For price inquiries, please feel free to contact us through the form on the left side. We will get back to you as soon as possible.

Downloads Newsletter. Reference: Adjei, I. Modulation of the tumor microenvironment for cancer treatment: a biomaterials approach. ADC Biochemical Analysis. ADC in vitro Efficacy Evaluation.Metrics details. Arterial stiffness is considered as an independent predictor of cardiovascular mortality, and is increasingly used in clinical practice. This study aimed at evaluating the consistency of the automated estimation of regional and local aortic stiffness indices from cardiovascular magnetic resonance CMR data.

Changes in aortic stiffness have a high physiopathological relevance as they can lead to increases in the aortic pulse pressure [ 12 ] and the cardiac pressure afterload, which can cause left ventricular hypertrophy [ 3 ]. Arterial stiffness is recognized as a major risk factor in coronary heart disease [ 45 ], and is considered as an independent predictor of cardiovascular mortality [ 6 — 10 ].

It is therefore increasingly used in clinical practice [ 11 ]. Distensibility and pulse wave velocity PWV are commonly used to characterize the arterial stiffness [ 12 — 16 ].

The distensibility describes the ability of the artery to expand during systole, and is defined as the relative change in the cross-sectional area of the artery strain divided by the local pulse pressure. The PWV is the propagation speed of the pressure or the velocity wave along the artery, and is calculated as the ratio between the distance separating two locations and the transit time needed for the wave to cover this distance.

Tonometry is the most commonly used technique for quantification of global vascular function [ 11 ]. However, this technique can only provide a global estimation of the aortic PWV, along the whole carotid-femoral artery path.

Indeed, tonometry uses body surface anatomy to estimate artery length and does not take into account the often torturous route of the vessels.

Cardiovascular magnetic resonance CMR is increasingly used to analyze the local and regional mechanical properties of the aortic wall and the blood flow [ 13 — 24 ]. Steady-state free-precession SSFP cine acquisitions enable a direct estimation of the aortic strain at localized and specific levels of the thoracic aorta, as well as the precise measurement of the length of the aorta.

Furthermore, phase-contrast PC cine acquisitions provide an accurate assessment of the blood flow velocities throughout different aortic sections during the cardiac cycle, which enable the estimation of velocity waveforms. The transit time of a velocity waveform propagation between two aortic sections can be calculated and its combination with the aortic distance travelled by the waveform provides the aortic arch PWV[ 15 ].

The combination of the aortic strain with pulse pressure measurements results in local aortic distensibility. Although the relation between the aortic strain and the distending pressure is complex because the aorta may exhibit a non-linear and spatially non-uniform elastic behavior, a theoretical model that links the PWV, strain, pulse pressure, and blood density have been proposed by Bramwell and Hill [ 25 ] and have been commonly used in clinical practice [ 11 ].

Despite the fact that the Bramwell and Hill equation was derived from the Moens-Korteweg equation [ 26 ], more modern theoretical work using the 1-D equations describing flow in compliant vessels [ 26 ] shows that the Bramwell-Hill model is more general since it does not consider assumptions such as thin-walled and homogeneous elastic arteries that are assumed in the Moens-Korteweg model.

Accordingly, our primary goal was to use the theoretical model described by Bramwell and Hill [ 25 ] to demonstrate the consistency of the automated MR measurements of the local and regional aortic stiffness indices.

None of the volunteers had any history of cardiovascular events or hypertension. All CMR examinations were performed on a 1.Whether it is the industrial smart robot in the age of IIoT using three dimensional data to orient itself in its working space, the reverse vending machine counting empty bottles in a case, or the surface inspection system alerting personnel to the smallest material defect - three dimensional information acquired by modern 3D sensors from the environment and the objects therein belongs to many industrial applications of the future.

Currently, there are a variety of technologies on the market which can be used to collect three-dimensional information from a scene. One critical point of differentiation which must be made among them, however, is between active and passive techniques: active techniques such as Lidar Light detection and ranging or time-of-flight sensors use an active light source in order to provide distance information; passive techniques, however, rely solely upon the camera-acquired image data - similar to depth perception in human visual systems.

All of the techniques each have their advantages and disadvantages: so while time-of-flight systems as a rule use less computational power and have few limitations in terms of scene structure, the maximum spatial resolution of current ToF systems x pixels is relatively low and their outdoor use very limited due to infrared radiation from the sun. Newer sensors on the market, however, have now enabled passive multi-view stereo vision systems to offer very high spatial resolution; they are, however, processor intensive and perform poorly when confronted with low-contrast or repeated textures.

Nevertheless, today's computational resources as well as optional pattern projectors make real-time operation of stereo systems at high spatial and depth resolutions possible. Precisely for this reason, passive multi-view stereo systems are among the most popular and flexible systems for the acquisition of 3D information. Multi-view stereo systems consist of two or more cameras which simultaneously record data from a scene.

When the cameras are calibrated and can be focused on a real-world point in the scene whose pixel can be located in the camera, a three-dimensional feature can then be reconstructed from the pixels via triangulation. The highest-possible level of precision which can be obtained depends on the distance between the cameras baselinethe convergence angle between the cameras, the sensor's pixel size and the focal length.

The essential aspects of calibration and correspondence matching alone make great demands on the underlying image processing algorithms. Through camera calibration, the position and orientation of the individual cameras can be determined external parameters as well as the focal length, principal point and distortion parameters internal parameters which are significantly influenced by the selected lenses.

Camera calibration is usually performed by using a two-dimensional calibration pattern such as a checkerboard or dots in which control points can be easily and clearly detected. Where, of course, the measurements of the calibration pattern such as the distances between control points are precisely known.

Next, image sequences of the calibration patterns with varying positions of pattern and orientation are made. Image processing algorithms detect the control points in the calibration pattern from the individual images. Edge and corner detection algorithms serve, for example, as the basis when using a checker board pattern and blob detection algorithms when using a dot calibration pattern. In so doing, a multitude of 3D-2D correspondences between the calibration object and the individual images emerge.

Based on these correspondences, an optimization process subsequently delivers the camera parameters. While the calibration is run only once assuming the camera parameters do not change during system operationthe significantly more processor-intensive task of finding correspondences between the views must be carried out for each image in order to deliver the scene's 3D information.

In the case of a stereo system, correspondences between two views are identified. In preprocessing, the images are usually rectified by means of the internal distortion parameters. For a pixel in the reference image, there will be a subsequent search for the corresponding point in the target image which represents the same 3D coordinate in the observed scene. Assuming Lambertian reflectance i. The correlation is computed between the source and the target region and indicates similarity.

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This is not the same as computing the correlation coefficients beforehand and comparing them afterwards normalized cross-correlation is well-established. The normalized cross-correlation is one such similarity measure. All available scene points are not needed for the target image: geometrically there are potentially corresponding points which lie in the rectified views on a line, a so-called epipolar line. Correspondences need only to be searched for along these epipolar lines.

In order to additionally accelerate the search, undistorted input images are often rectified. The input images are transformed so that all corresponding epipolar lines share the same vertical image coordinates.

Accordingly, for any given point in the reference image, one need only search along the line with the same vertical coordinate when looking for correspondences in the target image. While the algorithmic complexity of the search remains the same, the previous rectification allows for a more efficient search for correspondences. Furthermore, if the minimum and maximum working distances of the scene are known, the search can be additionally refined along the epipolar lines in order to accelerate it.

If all possible target environments along the epipolar lines have been compared with the reference environments, the target environment with the greatest similarity is, as a rule in the case of local stereo algorithmsselected as the final correspondence. If the correspondence search is complete, assuming that a clear correspondence has been found, for every pixel of the reference image in a rectified stereo vision system there will be the distance information in the form of the disparity - in other words, as the offset in pixels along the epipolar line.

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