3D Translation Research Articles

Simulation of the Magnetic Signature for Ferromagnetic Objects in Motion Using 3D-Printing Data

Investigations of the magnetic signature for ferromagnetic objects are extremely important in many areas. Some famous software can calculate the magnetic signature generated by the 3D ferromagnetic objects in motion, but they require tremendous computational time and large numerical resources. Therefore, we propose a simulation method whose core idea is to approximate the ferromagnetic object by a collection of magnetic dipoles whose placement is identified with the tool path information generated by 3D printing software and calculate the magnetic signature of the ferromagnetic object using the superposition principle. In view of the fact that each particle of a rigid body has the same laws of motion while the body moving and rotating in 3D space, coordinate translations, and rotations are used to implement the six-degrees-of-freedom movement of ferromagnetic objects. The simulations with a static object and objects in motion in the application of the magnetic test for a satellite validate the correctness of the proposed method. The evaluation of magnetic interference of a survey ship demonstrates the effectiveness. The method is easy to implement and has strong practicability and powerful expansibility.

Tongue–Computer Interface Prototype Design Based on T-Type Magnet Localization for Smart Environment Control

The interactions between paralyzed individuals with severe physical disabilities and smart infrastructure need to be facilitated, and the tongue–computer interface (TCI) provides an efficient and feasible solution. By attaching a permanent magnet (PM) on the apex of the tongue, the real-time tongue motion tracking can be switching to solve a nonlinear inverse magnetic problem. This paper presents a proof-of-concept prototype TCI system utilizing a combined T-type PM marker for potential environment control. The introduction of the combined T-type PM promotes the anisotropy of the magnetic field distribution. A comprehensive calibration method for the sensing system is proposed to figure out the bias in the magnetic moment of the PM marker and the sensing axis rotation of the sensors. To address the influence of initialization in solving the overdetermined inverse magnetic problem, an adaptive Levenberg–Marquardt algorithm is designed utilizing real-time measurements. Bench-top experiments were carried out based on a high-precision three-dimensional (3D) translation platform, and the feasibility of the proposed TCI system in magnetic localization accuracy and efficiency is fully assessed. The mean localization error is 1.65 mm with a mean processing time of 65.7 ms, and a mean improvement of 54.7% can be achieved compared with a traditional LM algorithm.

Assessing Reliability of Myocardial Blood Flow After Motion Correction With Dynamic PET Using a Bayesian Framework.

The estimation of myocardial blood flow (MBF) in dynamic PET can be biased by many different processes. A major source of error, particularly in clinical applications, is patient motion. Patient motion, or gross motion, creates displacements between different PET frames as well as between the PET frames and the CT-derived attenuation map, leading to errors in MBF calculation from voxel time series. Motion correction techniques are challenging to evaluate quantitatively and the impact on MBF reliability is not fully understood. Most metrics, such as signal-to-noise ratio (SNR), are characteristic of static images, and are not specific to motion correction in dynamic data. This study presents a new approach of estimating motion correction quality in dynamic cardiac PET imaging. It relies on calculating a MBF surrogate, K1 , along with the uncertainty on the parameter. This technique exploits a Bayesian framework, representing the kinetic parameters as a probability distribution, from which the uncertainty measures can be extracted. If the uncertainty extracted is high, the parameter studied is considered to have high variability - or low confidence - and vice versa. The robustness of the framework is evaluated on simulated time activity curves to ensure that the uncertainties are consistently estimated at the multiple levels of noise. Our framework is applied on 40 patient datasets, divided in 4 motion magnitude categories. Experienced observers manually realigned clinical datasets with 3D translations to correct for motion. K1 uncertainties were compared before and after correction. A reduction of uncertainty after motion correction of up to 60% demonstrates the benefit of motion correction in dynamic PET and as well as provides evidence of the usefulness of the new method presented.

An augmented correlation framework for the estimation of tumour translational and rotational motion during external beam radiotherapy treatments using intermittent monoscopic x-ray imaging and an external respiratory signal

Increasing evidence shows that intrafraction tumour motion monitoring must include both six degrees of freedom (6DoF): 3D translations and 3D rotations. Existing real-time algorithms for 6DoF target motion estimation require continuous intrafraction fluoroscopic imaging at high frequency, thereby exposing patients to additional high imaging dose. This paper presents the first method capable of 6DoF motion monitoring using intermittent 2D kV imaging and a continuous external respiratory signal.Our approach is to optimise a state-augmented linear correlation model between an external signal and internal 6DoF motion. In standard treatments, the model can be built using information obtained during pre-treatment cone beam CT (CBCT). Real-time 6DoF tumor motion can then be estimated using just the external signal. Intermittent intrafraction kV images are used to update the model parameters, accounting for changes in correlation and baseline shifts.The method was evaluated in silico using data from 6 lung SABR patients, with the internal tumour motion recorded with electromagnetic beacons and the external signal from a bellows belt. Projection images from CBCT (10 Hz) and intermittent kV images were simulated by projecting the 3D Calypso beacon positions onto an imager. IMRT and VMAT treatments were simulated with increasing imaging update intervals: 0.1 s, 1 s, 3 s, 10 s and 30 s.For all the tested clinical scenarios, translational motion estimates with our method had sub-mm accuracy (mean) and precision (standard deviation) while rotational motion estimates were accurate to < and precise to . Motion estimation errors increased as the imaging update interval increased. With the largest imaging update interval (30 s), the errors were mm, mm and mm for translation in the left–right, superior–inferior and anterior–posterior directions, respectively, and , and for rotation around the aforementioned axes for both VMAT and IMRT treatments.In conclusion, we developed and evaluated a novel method for highly accurate real-time 6DoF motion monitoring on a standard linear accelerator without requiring continuous kV imaging. The proposed method achieved sub-mm and sub-degree accuracy on a lung cancer patient dataset.

A JOINT EFFORT OF SPEEDED-UP ROBUST FEATURES ALGORITHM AND A DISPARITY-BASED MODEL FOR 3D INDOOR MAPPING USING RGB-D DATA

Abstract In this paper, we present a method for 3D mapping of indoor environments using RGB-D data. The contribution of our proposed method is two-fold. First, our method exploits a joint effort of the speed-up robust features (SURF) algorithm and a disparity-to-plane model for a coarse-to-fine registration procedure. Once the coarse-to-fine registration task accumulates errors, the same features can appear in two different locations of the map. This is known as the loop closure problem. Then, the variance-covariance matrix that describes the uncertainty of transformation parameters (3D rotation and 3D translation) for view-based loop closure detection followed by a graph-based optimization are proposed to achieve a 3D consistent indoor map. To demonstrate and evaluate the effectiveness of the proposed method, experimental datasets obtained in three indoor environments with different levels of details are used. The experimental results shown that the proposed framework can create 3D indoor maps with an error of 11,97 cm into object space that corresponds to a positional imprecision around 1,5% at the distance of 9 m travelled by sensor.

A novel intra-fraction motion monitoring system for stereotactic radiosurgery: proof of concept

The purpose of this work is to develop a prototype system for continuous, three-dimensional (3D) monitoring of patient cranial motion during stereotactic radiosurgery. Using novel capacitive detector plates, the goal was to provide detection of cranial position inside a thermoplastic immobilizing mask, without relying on skin monitoring or use of ionizing radiation.A novel capacitive detector array was used to detect cranial translations with sub-millimeter accuracy. The array was comprised of four conductive plates arranged around the cranium. One superior plate was positioned at the cranial vertex, two lateral plates were positioned in sagittal planes at the lateral aspects of the cranium and one plate was located in a coronal plane anterior to the face. The system was calibrated by parameterizing a capacitive signal for each dimension as a function of spatial translation. The detector array performance was evaluated with the help of a volunteer in the absence of radiation. Separately, possible effects of electromagnetic interference and irradiation in the linac suite were assessed.Detector plates mounted at 1 cm original distance to the thermoplastic mask can detect sub-millimeter lateral and superior cranial motion. Detection of sub-millimeter anterior motion is possible when the plate is mounted closer to the patient (5–10 mm). No signal interference was observed when the capacitive array was irradiated.Our prototype detector array provides continuous, 3D translation detection with sub-millimeter precision. The signal provides sufficient signal to noise ratio and is stable in linac room environment and in direct radiation beam. The detector plate is sensitive to the position of the cranium inside a mask and offers the advantage of being insensitive to the mask itself. Future work will involve modifying the array to detect patient rotation.

The virtual screw: Concept, design and applications

The research work reported here was motivated by a class of two-limb parallel Schönflies-motion11These motions comprise four degrees of freedom: three translations and one rotation about one axis of fixed direction. generators, which offer simplicity, isostaticity, and symmetry. The crucial components required to construct a parallel two-limb robot of this class are a cylindrical drive, namely, a cylindrical motion generator, and a load-carrying link playing the role of the moving platform in parallel robots, with four degrees-of-freedom, i.e. 3D translation and rotation about a vertical axis, which operates based on the same cylindrical motion generator. However, the design requirements of such components call upon screw joints with an unusually large pitch, which are not available off-the-shelf; the authors thus propose a cable-driven virtual screw with an arbitrarily large pitch. This concept is elaborated on with regard to its various alternatives, each suitable for different circumstances and applications. Furthermore, the concept of variable-pitch virtual screw is introduced, which enables the designer to adapt the specification of the robot to any given task. In addition, the novel application of the virtual screw in the context of the architecture of Schönflies-motion generators is studied. Finally, the authors report the design and fabrication of two prototypes to conduct a comparison between the screw joint and the virtual screw.

Early estimation model for 3D-discrete indian sign language recognition using graph matching

Machine translation of sign language is a critical task of computer vision. In this work, we propose to use 3D motion capture technology for sign capture and graph matching for sign recognition. Two problems related to 3D sign matching are addressed in this work: (1) how to identify same signs with different number of motion frames and (2) sign extraction from a clutter of non-sign hand motions. These two problems make the 2D or 3D sign language machine translation a challenging task. We propose graph matching with early estimation model to address these problems in two phases. The first phase consists of intra graph matching for motion frame extraction, which retains motion intensive frames in database and query 3D videos. The second phase applies inter graph matching with early estimation model on motion extracted query and dataset 3D videos. The proposed model increases the speed of the graph matching algorithm in estimating a sign with fewer frames. To test the graph matching model, we recorded 350 words of Indian sign language with 3D motion capture technology. For testing 4 variations per sign are captured for all signs with 5 different signers at same, slower, faster hand speeds and sign mixed cluttered hand motions. The early estimation graph matching model is tested for accuracy and efficiency in classifying 3D signs with the two induced real time constraints. In addition to 3D sign language dataset, the proposed method is validated on five benchmark datasets and against the state-of-the-art graph matching methods.

Efficient contour match kernel

We propose a novel concept of asymmetric feature maps (AFM), which allows to evaluate multiple kernels between a query and database entries without increasing the memory requirements. To demonstrate the advantages of the AFM method, we derive an efficient contour match kernel – short vector image representation that, due to asymmetric feature maps, supports efficient scale and translation invariant sketch-based image retrieval. Unlike most of the short-code based retrieval systems, the proposed method provides the query localization in the retrieved image. The efficiency of the search is boosted by approximating a 2D translation search via trigonometric polynomial of scores by 1D projections. The projections are a special case of AFM. An order of magnitude speed-up is achieved compared to traditional trigonometric polynomials. The results are boosted by an image-based average query expansion approach and, without any learning, significantly outperform the state-of-the-art hand-crafted descriptors on standard benchmarks. Our method competes well with recent CNN-based approaches that require large amounts of labeled sketches, images and sketch-image pairs.

Growth study and characterization of KDP crystals grown by 2D translation method

Transparent potassium dihydrogen phosphate (KDP) crystals that are grown from different translational velocities and orientation configurations were obtained during growth through a novel motion mode called 2D translation method. The grown crystals were investigated by microhardness, dielectric, chemical etching, thermal analysis and laser damage threshold studies. A higher mechanical hardness is observed in crystals grown by the 2D translation method than that grown by the rotating-crystal method. Low dielectric loss and less dislocation density show that the 2D translation method grown crystals contain minimum defects. The thermal stability and damage threshold of the 2D translation method grown crystals are higher than those of the crystal grown using the rotating-crystal method. Moreover, the properties of various crystals grown by the 2D translation method under different conditions are compared, and results show that the grown crystals' quality is best when the translation velocity is 0.04 m/s.

A fiducial tag invariant to rotation, translation, and perspective transformations

This work introduces a novel visual fiducial tag appropriate for applications of automatic identification. The proposed tag is based in Order Type, a construction defined in Computational Geometry, which is invariant to 3D translation, rotation, and projective transformations. Three main contributions are presented: first we describe the design of the proposed tags, the procedures for detecting them from an image, and the algorithms for computing an identifier from them. Second, we analyze the feasibility of the proposal in three different conditions of tag’s rotation, distance to the tag, and the effect of noise in point positions for the recognition process. Third, we show the applicability of the proposed tags with simulated images. The conducted experiments indicate that the tags are very robust to the image generation process, suitable for automatic identification up to 3472 different tags, and also for the pose estimation in Computer Vision applications.

Rotation Scaling and Translation Invariants of 3D Radial Shifted Legendre Moments

This paper proposes a new set of 3D rotation scaling and translation invariants of 3D radially shifted Legendre moments. We aim to develop two kinds of transformed shifted Legendre moments: a 3D substituted radial shifted Legendre moments (3DSRSLMs) and a 3D weighted radial one (3DWRSLMs). Both are centered on two types of polynomials. In the first case, a new 3D radial complex moment is proposed. In the second case, new 3D substituted/weighted radial shifted Legendre moments (3DSRSLMs/3DWRSLMs) are introduced using a spherical representation of volumetric image. 3D invariants as derived from the suggested 3D radial shifted Legendre moments will appear in the third case. To confirm the proposed approach, we have resolved three issues. To confirm the proposed approach, we have resolved three issues: rotation, scaling and translation invariants. The result of experiments shows that the 3DSRSLMs and 3DWRSLMs have done better than the 3D radial complex moments with and without noise. Simultaneously, the reconstruction converges rapidly to the original image using 3D radial 3DSRSLMs and 3DWRSLMs, and the test of 3D images are clearly recognized from a set of images that are available in Princeton shape benchmark (PSB) database for 3D image.

The accuracy and precision of Kilovoltage Intrafraction Monitoring (KIM) six degree-of-freedom prostate motion measurements during patient treatments

Background and purposeTo perform a quantitative analysis of the accuracy and precision of Kilovoltage Intrafraction Monitoring (KIM) six degree-of-freedom (6DoF) prostate motion measurements during treatments. Material and methodsReal-time 6DoF prostate motion was acquired using KIM for 14 prostate cancer patients (377 fractions). KIM outputs the 6DoF prostate motion, combining 3D translation and 3D rotational motion information relative to its planning position. The corresponding groundtruth target motion was obtained post-treatment based on kV/MV triangulation. The accuracy and precision of the 6DoF KIM motion estimates were calculated as the mean and standard deviation differences compared with the ground-truth. ResultsThe accuracy ± precision of real-time 6DoF KIM−measured prostate motion were 0.2 ± 1.3° for rotations and 0.1 ± 0.5 mm for translations, respectively. The magnitude of KIM-measured motion was well-correlated with the magnitude of ground-truth motion resulting in Pearson correlation coefficients of ≥0.88 in all DoF. ConclusionsThe results demonstrate that KIM is capable of providing the real-time 6DoF prostate target motion during patient treatments with an accuracy ± precision of within 0.2 ± 1.3° and 0.1 ± 0.5 mm for rotation and translation, respectively. As KIM only requires a single X-ray imager, which is available on most modern cancer radiotherapy devices, there is potential for widespread adoption of this technology.

Dynamic kinematics of the glenohumeral joint in shoulders with rotator cuff tears

BackgroundNo clear trend has emerged from the literature regarding three-dimensional (3D) translations of the humerus relative to the scapula in shoulders with rotator cuff tears (RCTs). The purpose of this study was to evaluate the kinematics of RCT shoulders using 3D-to-two-dimensional (2D) model-to-image registration techniques.MethodsDynamic glenohumeral kinematics during scapular plane abduction and axial rotation were analyzed in 11 RCT patients and 10 healthy control subjects. We measured the 3D kinematic parameters of glenohumeral joints using X-ray images and CT-derived digitally reconstructed radiographs.ResultsFor scapular plane abduction, the humeral head center was positioned significantly more medially in shoulders with RCTs than in controls at 135° of humeral abduction (p = 0.02; RCTs versus controls: − 0.9 ± 1.6 versus 0.3 ± 1.3 mm). There was no significant difference in the superior/inferior translation of the humeral head center (p = 0.99). For axial rotation in adducted position, the humeral head center was positioned significantly more anteriorly in shoulders with RCTs than in controls at − 30° of glenohumeral external rotation (p < 0.0001; RCTs versus controls: 3.0 ± 1.7 versus 0.3 ± 1.5 mm).ConclusionsThis study revealed the kinematics of shoulders with large to massive full-thickness RCTs: the humeral head center showed a medial shift at the late phase of scapular plane full abduction, and an anterior shift at the internal rotation position during full axial rotation. The kinematic data in this study, which describe the patterns of movement of shoulders with large to massive full-thickness RCTs, provide valuable information for future studies investigating glenohumeral translations in other pathological conditions of the shoulder. For clinical relevance, quantitative assessment of the dynamic kinematics of shoulders with RCTs might be a therapeutic indicator for achieving functional restoration.

An interdimensional correlation framework for real-time estimation of six degree of freedom target motion using a single x-ray imager during radiotherapy

Increasing evidence suggests that intrafraction tumour motion monitoring needs to include both 3D translations and 3D rotations. Presently, methods to estimate the rotation motion require the 3D translation of the target to be known first. However, ideally, translation and rotation should be estimated concurrently. We present the first method to directly estimate six-degree-of-freedom (6DoF) motion from the target’s projection on a single rotating x-ray imager in real-time.This novel method is based on the linear correlations between the superior–inferior translations and the motion in the other five degrees-of-freedom. The accuracy of the method was evaluated in silico with 81 liver tumour motion traces from 19 patients with three implanted markers. The ground-truth motion was estimated using the current gold standard method where each marker’s 3D position was first estimated using a Gaussian probability method, and the 6DoF motion was then estimated from the 3D positions using an iterative method.The 3D position of each marker was projected onto a gantry-mounted imager with an imaging rate of 11 Hz. After an initial 110° gantry rotation (200 images), a correlation model between the superior–inferior translations and the five other DoFs was built using a least square method. The correlation model was then updated after each subsequent frame to estimate 6DoF motion in real-time.The proposed algorithm had an accuracy (±precision) of −0.03 ± 0.32 mm, −0.01 ± 0.13 mm and 0.03 ± 0.52 mm for translations in the left–right (LR), superior–inferior (SI) and anterior–posterior (AP) directions respectively; and, 0.07 ± 1.18°, 0.07 ± 1.00° and 0.06 ± 1.32° for rotations around the LR, SI and AP axes respectively on the dataset.The first method to directly estimate real-time 6DoF target motion from segmented marker positions on a 2D imager was devised. The algorithm was evaluated using 81 motion traces from 19 liver patients and was found to have sub-mm and sub-degree accuracy.

Three dimensional radial Tchebichef moment invariants for volumetric image recognition

The property of rotation, scaling and translation invariant has a great important in 3D image classification and recognition. Tchebichef moments as a classical orthogonal moment have been widely used in image analysis and recognition. Since Tchebichef moments are represented in Cartesian coordinate, the rotation invariance can’t easy to realize. In this paper, we propose a new set of 3D rotation scaling and translation invariance of radial Tchebichef moments. We also present a theoretical mathematics to derive them. Hence, this paper we present a new 3D radial Tchebichef moments using a spherical representation of volumetric image by a one-dimensional orthogonal discrete Tchebichef polynomials and a spherical function. They have better image reconstruction performance, lower information redundancy and higher noise robustness than the existing radial orthogonal moments. At last, a mathematical framework for obtaining the rotation, scaling and translation invariants of these two types of Tchebichef moments is provided. Theoretical and experimental results show the superiority of the proposed methods in terms of image reconstruction capability and invariant recognition accuracy under both noisy and noise-free conditions. The result of experiments prove that the Tchebichef moments have done better than the Krawtchouk moments with and without noise. Simultaneously, the reconstructed 3D image converges quickly to the original image using 3D radial Tchebichef moments and the test images are clearly recognized from a set of images that are available in a PSB database.

Development of real-time object motion estimation from single camera

We present a new approach for determining 3D motion of a moving rigid object relative to a single camera in image sequences. To estimate motion parameters as characterized by 3D rotation and 3D translation, non-linear least square equations have been formulated. Corresponding features on an object were observed from images at different times. Good initial values of these non-linear equations were provided from a para-perspective projection model to overcome ill-conditioned convergence problem of the equations.

Label-free 3D computational imaging of spermatozoon locomotion, head spin and flagellum beating over a large volume

We report a high-throughput and label-free computational imaging technique that simultaneously measures in three-dimensional (3D) space the locomotion and angular spin of the freely moving heads of microswimmers and the beating patterns of their flagella over a sample volume more than two orders-of-magnitude larger compared to existing optical modalities. Using this platform, we quantified the 3D locomotion of 2133 bovine sperms and determined the spin axis and the angular velocity of the sperm head, providing the perspective of an observer seated at the moving and spinning sperm head. In this constantly transforming perspective, flagellum-beating patterns are decoupled from both the 3D translation and spin of the head, which provides the opportunity to truly investigate the 3D spatio-temporal kinematics of the flagellum. In addition to providing unprecedented information on the 3D locomotion of microswimmers, this computational imaging technique could also be instrumental for micro-robotics and sensing research, enabling the high-throughput quantification of the impact of various stimuli and chemicals on the 3D swimming patterns of sperms, motile bacteria and other micro-organisms, generating new insights into taxis behaviors and the underlying biophysics.

Looking Beyond the Simple Scenarios: Combining Learners and Optimizers in 3D Temporal Tracking.

3D object temporal trackers estimate the 3D rotation and 3D translation of a rigid object by propagating the transformation from one frame to the next. To confront this task, algorithms either learn the transformation between two consecutive frames or optimize an energy function to align the object to the scene. The motivation behind our approach stems from a consideration on the nature of learners and optimizers. Throughout the evaluation of different types of objects and working conditions, we observe their complementary nature - on one hand, learners are more robust when undergoing challenging scenarios, while optimizers are prone to tracking failures due to the entrapment at local minima; on the other, optimizers can converge to a better accuracy and minimize jitter. Therefore, we propose to bridge the gap between learners and optimizers to attain a robust and accurate RGB-D temporal tracker that runs at approximately 2 ms per frame using one CPU core. Our work is highly suitable for Augmented Reality (AR), Mixed Reality (MR) and Virtual Reality (VR) applications due to its robustness, accuracy, efficiency and low latency. Aiming at stepping beyond the simple scenarios used by current systems, often constrained by having a single object in the absence of clutter, averting to touch the object to prevent close-range partial occlusion or selecting brightly colored objects to easily segment them individually, we demonstrate the capacity to handle challenging cases under clutter, partial occlusion and varying lighting conditions.

Passive lighting responsive three-dimensional integral imaging

A three dimensional (3D) integral imaging (II) technique with a real-time passive lighting responsive ability and vivid 3D performance has been proposed and demonstrated. Some novel lighting responsive phenomena, including light-activated 3D imaging, and light-controlled 3D image scaling and translation, have been realized optically without updating images. By switching the on/off state of a point light source illuminated on the proposed II system, the 3D images can show/hide independent of the diffused illumination background. By changing the position or illumination direction of the point light source, the position and magnification of the 3D image can be modulated in real time. The lighting responsive mechanism of the 3D II system is deduced analytically and verified experimentally. A flexible thin film lighting responsive II system with a 0.4 mm thickness was fabricated. This technique gives some additional degrees of freedom in order to design the II system and enable the virtual 3D image to interact with the real illumination environment in real time.