Spatiotemporal registration of multiple three-dimensional echocardiographic recordings for enhanced field of view imaging

This paper summarizes recent advances made by this group in the automated three-dimensional (3-D) image analysis of cytological specimens that are much thicker than the depth of field, and much wider than the field of view of the microscope. The imaging of thick samples is motivated by the need to sample large volumes of tissue rapidly, make more accurate measurements than possible with 2-D sampling, and also to perform analysis in a manner that preserves the relative locations and 3-D structures of the cells. The motivation to study specimens much wider than the field of view arises when measurements and insights at the tissue, rather than the cell level are needed.The term “analysis” indicates a activities ranging from cell counting, neuron tracing, cell morphometry, measurement of tracers, through characterization of large populations of cells with regard to higher-level tissue organization by detecting patterns such as 3-D spatial clustering, the presence of subpopulations, and their relationships to each other. Of even more interest are changes in these parameters as a function of development, and as a reaction to external stimuli. There is a widespread need to measure structural changes in tissue caused by toxins, physiologic states, biochemicals, aging, development, and electrochemical or physical stimuli. These agents could affect the number of cells per unit volume of tissue, cell volume and shape, and cause structural changes in individual cells, inter-connections, or subtle changes in higher-level tissue architecture. It is important to process large intact volumes of tissue to achieve adequate sampling and sensitivity to subtle changes. It is desirable to perform such studies rapidly, with utmost automation, and at minimal cost. Automated 3-D image analysis methods offer unique advantages and opportunities, without making simplifying assumptions of tissue uniformity, unlike random sampling methods such as stereology.12 Although stereological methods are known to be statistically unbiased, they may not be statistically efficient. Another disadvantage of sampling methods is the lack of full visual confirmation - an attractive feature of image analysis based methods.

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A survey on stereo vision-based autonomous navigation for multi-rotor MUAVs

Robotica ◽

10.1017/s0263574718000358 ◽

2018 ◽

Vol 36 (8) ◽

pp. 1225-1243 ◽

Cited By ~ 5

Author(s):

Jose-Pablo Sanchez-Rodriguez ◽

Alejandro Aceves-Lopez

Keyword(s):

Unmanned Aerial Vehicles ◽

Stereo Vision ◽

Autonomous Navigation ◽

Three Dimensional ◽

Field Of View ◽

Line Of Sight ◽

Onboard Computer ◽

Low Weight ◽

Vision Based Navigation ◽

Difficult Challenge

SUMMARYThis paper presents an overview of the most recent vision-based multi-rotor micro unmanned aerial vehicles (MUAVs) intended for autonomous navigation using a stereoscopic camera. Drone operation is difficult because pilots need the expertise to fly the drones. Pilots have a limited field of view, and unfortunate situations, such as loss of line of sight or collision with objects such as wires and branches, can happen. Autonomous navigation is an even more difficult challenge than remote control navigation because the drones must make decisions on their own in real time and simultaneously build maps of their surroundings if none is available. Moreover, MUAVs are limited in terms of useful payload capability and energy consumption. Therefore, a drone must be equipped with small sensors, and it must carry low weight. In addition, a drone requires a sufficiently powerful onboard computer so that it can understand its surroundings and navigate accordingly to achieve its goal safely. A stereoscopic camera is considered a suitable sensor because of its three-dimensional (3D) capabilities. Hence, a drone can perform vision-based navigation through object recognition and self-localise inside a map if one is available; otherwise, its autonomous navigation creates a simultaneous localisation and mapping problem.

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Calibration of the Relative Orientation between Multiple Depth Cameras Based on a Three-Dimensional Target

Sensors ◽

10.3390/s19133008 ◽

2019 ◽

Vol 19 (13) ◽

pp. 3008 ◽

Cited By ~ 1

Author(s):

Zhe Liu ◽

Zhaozong Meng ◽

Nan Gao ◽

Zonghua Zhang

Keyword(s):

Coordinate System ◽

Camera Calibration ◽

Three Dimensional ◽

Field Of View ◽

Depth Information ◽

Depth Camera ◽

Depth Cameras ◽

Calibration Methods ◽

3D Shape Reconstruction ◽

Single Coordinate

Depth cameras play a vital role in three-dimensional (3D) shape reconstruction, machine vision, augmented/virtual reality and other visual information-related fields. However, a single depth camera cannot obtain complete information about an object by itself due to the limitation of the camera’s field of view. Multiple depth cameras can solve this problem by acquiring depth information from different viewpoints. In order to do so, they need to be calibrated to be able to accurately obtain the complete 3D information. However, traditional chessboard-based planar targets are not well suited for calibrating the relative orientations between multiple depth cameras, because the coordinates of different depth cameras need to be unified into a single coordinate system, and the multiple camera systems with a specific angle have a very small overlapping field of view. In this paper, we propose a 3D target-based multiple depth camera calibration method. Each plane of the 3D target is used to calibrate an independent depth camera. All planes of the 3D target are unified into a single coordinate system, which means the feature points on the calibration plane are also in one unified coordinate system. Using this 3D target, multiple depth cameras can be calibrated simultaneously. In this paper, a method of precise calibration using lidar is proposed. This method is not only applicable to the 3D target designed for the purposes of this paper, but it can also be applied to all 3D calibration objects consisting of planar chessboards. This method can significantly reduce the calibration error compared with traditional camera calibration methods. In addition, in order to reduce the influence of the infrared transmitter of the depth camera and improve its calibration accuracy, the calibration process of the depth camera is optimized. A series of calibration experiments were carried out, and the experimental results demonstrated the reliability and effectiveness of the proposed method.

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The evolution of cephalometric diagnosis in Orthodontics

Dental Press Journal of Orthodontics ◽

10.1590/s2176-94512013000300011 ◽

2013 ◽

Vol 18 (3) ◽

pp. 63-71 ◽

Cited By ~ 4

Author(s):

Maurício Barbosa Guerra da Silva ◽

Eduardo Franzotti Sant'Anna

Keyword(s):

Computed Tomography ◽

Diagnostic Imaging ◽

Orthognathic Surgery ◽

Three Dimensional ◽

Field Of View ◽

Radiation Doses ◽

Radiographic Image ◽

Three Dimensional Images

INTRODUCTION: Although the development of CT have represented a landmark in diagnostic imaging, its use in Dentistry turned out very discretely over the years. With the appearance of programs for analysis of three-dimensional images, specific for Orthodontics and Orthognathic surgery, a new reality is being built. OBJECTIVE: The authors of this study aim to inform the orthodontic society of fundamentals about digital cephalometric radiographic image and computed tomography, discussing about: Field of view (FOV), radiation doses, demands for the use in Orthodontics and radiographic simulations.

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A Registration Method for Three-Dimensional Analysis of Bone Mineral Density in the Proximal Tibia

Journal of Biomechanical Engineering ◽

10.1115/1.4048335 ◽

2020 ◽

Vol 143 (1) ◽

Author(s):

Hugo Babel ◽

Loïc Wägeli ◽

Berke Sonmez ◽

Jean-Philippe Thiran ◽

Patrick Omoumi ◽

...

Keyword(s):

Bone Mineral Density ◽

Bone Mineral ◽

Proximal Tibia ◽

Three Dimensional ◽

Field Of View ◽

3D Analysis ◽

Mineral Density ◽

Comprehensive Description ◽

Registration Method ◽

The Relationship

Abstract Although alterations in bone mineral density (BMD) at the proximal tibia have been suggested to play a role in various musculoskeletal conditions, their pathophysiological implications and their value as markers for diagnosis remain unclear. Improving our understanding of proximal tibial BMD requires novel tools for three-dimensional (3D) analysis of BMD distribution. Three-dimensional imaging is possible with computed tomography (CT), but computational anatomy algorithms are missing to standardize the quantification of 3D proximal tibial BMD, preventing distribution analyses. The objectives of this study were to develop and assess a registration method, suitable with routine knee CT scans, to allow the standardized quantification of 3D BMD distribution in the proximal tibia. Second, as an example of application, the study aimed to characterize the distribution of BMD below the tibial cartilages in healthy knees. A method was proposed to register both the surface (vertices) and the content (voxels) of proximal tibias. The method combines rigid transformations to account for differences in bone size and position in the scanner's field of view and to address inconsistencies in the portion of the tibial shaft included in routine CT scan, with a nonrigid transformation locally matching the proximal tibias. The method proved to be highly reproducible and provided a comprehensive description of the relationship between bone depth and BMD. Specifically it reported significantly higher BMD in the first 6 mm of bone than deeper in the proximal tibia. In conclusion, the proposed method offers promising possibilities to analyze BMD and other properties of the tibia in 3D.

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Three-dimensional impact angle control guidance with field-of-view constraint

Aerospace Science and Technology ◽

10.1016/j.ast.2020.106014 ◽

2020 ◽

Vol 105 ◽

pp. 106014

Author(s):

Bojun Liu ◽

Mingshan Hou ◽

Ying Yu ◽

Zhonghua Wu

Keyword(s):

Three Dimensional ◽

Impact Angle ◽

Field Of View

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First Data from a Commercial Local Electrode Atom Probe (LEAP)

Microscopy and Microanalysis ◽

10.1017/s1431927604040565 ◽

2004 ◽

Vol 10 (3) ◽

pp. 373-383 ◽

Cited By ~ 151

Author(s):

Thomas F. Kelly ◽

Tye T. Gribb ◽

Jesse D. Olson ◽

Richard L. Martens ◽

Jeffrey D. Shepard ◽

...

Keyword(s):

Data Collection ◽

Three Dimensional ◽

Atom Probe ◽

Field Of View ◽

Performance Parameters ◽

Scientific Instruments ◽

Materials Analysis ◽

Collection Rate ◽

Atom Probes

The first dedicated local electrode atom probes (LEAP [a trademark of Imago Scientific Instruments Corporation]) have been built and tested as commercial prototypes. Several key performance parameters have been markedly improved relative to conventional three-dimensional atom probe (3DAP) designs. The Imago LEAP can operate at a sustained data collection rate of 1 million atoms/minute. This is some 600 times faster than the next fastest atom probe and large images can be collected in less than 1 h that otherwise would take many days. The field of view of the Imago LEAP is about 40 times larger than conventional 3DAPs. This makes it possible to analyze regions that are about 100 nm diameter by 100 nm deep containing on the order of 50 to 100 million atoms with this instrument. Several example applications that illustrate the advantages of the LEAP for materials analysis are presented.

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Confidence in Assessment of Lumbar Spondylolysis Using Three-Dimensional Volumetric T2-Weighted MRI Compared With Limited Field of View, Decreased-Dose CT

Sports Health A Multidisciplinary Approach ◽

10.1177/1941738116653587 ◽

2016 ◽

Vol 8 (4) ◽

pp. 364-371 ◽

Cited By ~ 4

Author(s):

Joshua Adam Delavan ◽

Nicholas V. Stence ◽

David M. Mirsky ◽

Jane Gralla ◽

Michael F. Fadell

Keyword(s):

Three Dimensional ◽

Field Of View ◽

Lumbar Spondylolysis

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Calibration of a three-dimensional photodynamic therapy illumination system and its segmentation assessment for port-wine stains

Photonics and Lasers in Medicine ◽

10.1515/plm-2016-0014 ◽

2016 ◽

Vol 5 (3) ◽

Author(s):

Yun Feng ◽

Xiaoming Hu ◽

Ya Zhou ◽

Yong Wang

Keyword(s):

Photodynamic Therapy ◽

Three Dimensional ◽

Calibration Method ◽

Field Of View ◽

Utilization Rate ◽

Color Coding ◽

Light Dosimetry ◽

Illumination System ◽

Low Field ◽

Fine Distinction

AbstractThe uniformity of light dosimetry is an important parameter that affects the efficacy of photodynamic therapy (PDT). Although this uniformity can be improved by a three-dimensional (3D) digital PDT illumination system, it has a low field-of-view (FOV) utilization rate. A checkerboard calibration method using color coding is proposed to calibrate both the projector and camera of the system with a broad common FOV. Experiments reveal that the proposed method increases the utilization rate by up to three times compared with noncolor-coding methods with almost the same accuracy. A fine distinction of phantom lesions in the 3D system can be obtained by clustering, which may be used to optimize the treatment and light-dosimetry evaluation.

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Three-Dimensional Stitching of Binocular Endoscopic Images Based on Feature Points

Photonics ◽

10.3390/photonics8080330 ◽

2021 ◽

Vol 8 (8) ◽

pp. 330

Author(s):

Changjiang Zhou ◽

Hao Yu ◽

Bo Yuan ◽

Liqiang Wang ◽

Qing Yang

Keyword(s):

Point Cloud ◽

Three Dimensional ◽

Point Clouds ◽

Field Of View ◽

Small Field ◽

Feature Points ◽

Endoscopic Image ◽

Left And Right ◽

Conventional Algorithm ◽

Small Field Of View

There are shortcomings of binocular endoscope three-dimensional (3D) reconstruction in the conventional algorithm, such as low accuracy, small field of view, and loss of scale information. To address these problems, aiming at the specific scenes of stomach organs, a method of 3D endoscopic image stitching based on feature points is proposed. The left and right images are acquired by moving the endoscope and converting them into point clouds by binocular matching. They are then preprocessed to compensate for the errors caused by the scene characteristics such as uneven illumination and weak texture. The camera pose changes are estimated by detecting and matching the feature points of adjacent left images. Finally, based on the calculated transformation matrix, point cloud registration is carried out by the iterative closest point (ICP) algorithm, and the 3D dense reconstruction of the whole gastric organ is realized. The results show that the root mean square error is 2.07 mm, and the endoscopic field of view is expanded by 2.20 times, increasing the observation range. Compared with the conventional methods, it does not only preserve the organ scale information but also makes the scene much denser, which is convenient for doctors to measure the target areas, such as lesions, in 3D. These improvements will help improve the accuracy and efficiency of diagnosis.

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