1733 results about "Reconstruction algorithm" patented technology

An automated three dimensional mapping and display system for a diagnostic ultrasound system is presented. According to the invention, ultrasound probe position registration is automated, the position of each pixel in the ultrasound image in reference to selected anatomical references is calculated, and specified information is stored on command. The system, during real time ultrasound scanning, enables the ultrasound probe position and orientation to be continuously displayed over a body or body part diagram, thereby facilitating scanning and images interpretation of stored information. The system can then record single or multiple ultrasound free hand two-dimensional (also “2D”) frames in a video sequence (clip) or cine loop wherein multiple 2D frames of one or more video sequences corresponding to a scanned volume can be reconstructed in three-dimensional (also “3D”) volume images corresponding to the scanned region, using known 3D reconstruction algorithms. In later examinations, the exact location and position of the transducer can be recreated along three dimensional or two dimensional axis points enabling known targets to be viewed from an exact, known position.

A photoacoustic imaging apparatus is provided for medical or other imaging applications and also a method for calibrating this apparatus. The apparatus employs a sparse array of transducer elements and a reconstruction algorithm. Spatial calibration maps of the sparse array are used to optimize the reconstruction algorithm. The apparatus includes a laser producing a pulsed laser beam to illuminate a subject for imaging and generate photoacoustic waves. The transducers are fixedly mounted on a holder so as to form the sparse array. A photoacoustic (PA) waves are received by each transducer. The resultant analog signals from each transducer are amplified, filtered, and converted to digital signals in parallel by a data acquisition system which is operatively connected to a computer. The computer receives the digital signals and processes the digital signals by the algorithm based on iterative forward projection and back-projection in order to provide the image.

A multi-layer dental panoramic and transverse x-ray imaging system includes an x-ray source; a digital imaging device capable of frame mode output with a sufficient frame rate; a mechanical manipulator having at least one rotational axis located in a position other than the focal point of the x-ray source; a position detection mechanism for detecting the camera position in 1D, 2D or 3D depending of the complexity of the trajectory; a final image reconstruction mechanism for reconstructing the final images out of the stored frames; a real time storage system such as RAM, hard drive or an drive array able to store all the frames captured during an exposure; and a digital processing unit capable of executing the reconstruction algorithm, such components being interconnected in operational arrangement. The system produces selectively dental panoramic x-ray images, dental transverse x-ray images and dental tomosynthetic 3D images from a frame stream produced by a high-speed, x-ray digital imaging device.

A transmission wave field imaging method, comprising the transmission of an incident wave field into an object, the incident wave field propagating into the object and, at least, partially scattering. Also includes the measuring of a wave field transmitted, at least in part, through an object to obtain a measured wave field, the measured wave field based, in part, on the incident wave field and the object. Additionally, the processing of the measured wave field utilizing a parabolic approximation reconstruction algorithm to generate an image data set representing at least one image of the object.

The shapes of many natural or man-made objects have curve features. The images of such curves usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. In this paper, we introduce a photogrammetric method for recovering free-form objects with curvilinear structures. Our method chooses to define the topology and recover a sparse 3D wireframe of the object first instead of directly recovering a surface or volume model. Surface patches covering the object are then constructed to interpolate the curves in this wireframe while satisfying certain heuristics such as minimal bending energy. The result is an object surface model with curvilinear structures from a sparse set of images. We can produce realistic texture-mapped renderings of the object model from arbitrary viewpoints. Reconstruction results on multiple real objects are presented to demonstrate the effectiveness of our approach.

A transmission wave field imaging method, comprising the transmission of an incident wave field into an object, the incident wave field propagating into the object and, at least, partially scattering. Also includes the measuring of a wave field transmitted, at least in part, through an object to obtain a measured wave field, the measured wave field based, in part, on the incident wave field and the object. Additionally, the processing of the measured wave field utilizing a parabolic approximation reconstruction algorithm to generate an image data set representing at least one image of the object.

A system and method for processing and storing personal information in a secure manner is described. In particular, a system and method for processing, splitting and storing genomic information or portions thereof in a secure electronic format is disclosed. An individual's genomic sequence is digitized and a splitting algorithm applied to fragment and randomise the digitized genomic information into at least two separate datasets. One dataset is retained by the individual and the second dataset is stored on a central server as a secure database record. Each dataset in isolation presents uninformative data and it is only when both datasets are combined, using a reconstruction algorithm to recombine the separate dataset data for an individual that the digitized data is capable of being presented into a useable and informative format.

The invention belongs to crossing field of computer vision and intelligent robots and discloses a variational mechanism-based large-area indoor scene reconstruction method. The method comprises the following steps: step 1, acquiring calibration parameters of a camera, and building an aberration correcting model; step 2, building a camera position and gesture depiction and camera projection model; step 3, utilizing an SFM-based monocular SFM (Space Frequency Modulation) algorithm to realize camera position and gesture estimation; step 4, building a variational mechanism-based depth map estimation model, and performing solving on the model; and step 5, building a key frame selection mechanism to realize three-dimensional scene renewal. According to the invention, an RGB (Red Green Blue) camera is adopted to acquire environmental data, and a variational mechanism-based depth map generation method is proposed through utilizing a high-precision monocular positioning algorithm, so that quick large-area indoor three-dimensional scene reconstruction is realized, and problems of three-dimensional reconstruction algorithm cost and real-time performance are effectively solved.

The present invention provides a computer system and user interface that allows a user to readily view and analyze two-dimensional and three-dimensional in vivo images and imaging data. The user interface is well-suited for one or more of the following actions pertinent to in vivo light imaging: investigation and control of three-dimensional imaging data and reconstruction algorithms; control of topographic reconstruction algorithms; tomographic spectral imaging and analysis; and comparison of two-dimensional or three-dimensional imaging data obtained at different times.

A transmission wave field imaging method, comprising the transmission of an incident wave field into an object, the incident wave field propagating into the object and, at least, partially scattering. Also includes the measuring of a wave field transmitted, at least in part, through an object to obtain a measured wave field, the measured wave field based, in part, on the incident wave field and the object. Additionally, the processing of the measured wave field utilizing a recursive reconstruction algorithm to generate an image data set representing at least one image of the object.

The invention discloses an image super-resolution reconstruction algorithm based on a shallow convolution neural network and a deep convolution neural network. The method comprises the following steps: 1) selecting a training sample and a testing sample; 2) performing extracting, mapping, upsamping and multi-scale conversion to the deep network characteristics; 3) extracting the characteristics of the shallow network; and 4) combining the shallow network and the deep network. Compared with the prior art, with regard to the single image reconstruction and video sequence reconstruction, the algorithm of the invention can accurately and effectively reconstruct the model of a high-resolution image so as to obtain a good reconstruction effect. In addition, multi-scale detail characteristic extraction is achieved, and the algorithm has better results than that of other existing algorithms. The reconstruction speed is also fast.

An object three-dimensional outline measurement device and a measurement method are disclosed, the device is composed of a laser diode, a lens, an aperture diaphragm, a two-dimensional Dammam grating, a cylindrical mirror and an area array CCD camera, a transmission line and a computer, the connection relationship therebetween is as below: a beam emitted by the laser diode passes through the lens, the aperture diaphragm, the two-dimensional Dammam grating, and the cylindrical mirror sequentially to form one-dimensional projection array stripes, which illuminates the surface of an objective to be measured, the area array CCD camera collects the grating projection strips modulated by three-dimensional digital shape on the surface of the measured objective and outputs the strips to the computer via the transmission line, the computer includes an image collecting interface, image collecting software and three-dimensional measurement information reconstruction algorithm software. The invention has, by utilizing the Fourier transform three-dimensional outline measurement structure, the advantages of high energy utilization rate, simple measurement structure, high measurement precision, convenient computer reconstruction information processing and great easiness for operation.

A transmission wave field imaging method, comprising the transmission of an incident wave field into an object, the incident wave field propagating into the object and, at least, partially scattering. Also includes the measuring of a wave field transmitted, at least in part, through an object to obtain a measured wave field, the measured wave field based, in part, on the incident wave field and the object. Additionally, the processing of the measured wave field utilizing a parabolic approximation reconstruction algorithm to generate an image data set representing at least one image of the object.

An extra-oral digital panoramic dental x-ray imaging system is disclosed for multi-layer panoramic and transverse X-ray imaging. The system includes an X-ray source and a digital imaging device capable of “real time” frame mode output. The source and imaging device are mounted in a mechanical manipulator defining the trajectory of a predetermined image layer. The imaging device communicates with a processor that generates a frames memory from which an image reconstruction mechanism composes the final images. For “real time” imaging, the frames memory is a fast data storage system such as RAM. The processing unit executes the reconstruction algorithms, allowing the system to selectively generate dental panoramic X-ray images, dental transverse x-ray images and dental tomosynthetic 3D images.

The invention belongs to the crossing field of computer vision and intelligent robots, relates to an indoor three-dimensional scene rebuilding method based on a double-layer rectification method and solves the problems that an existing indoor scene rebuilding method is expensive in required equipment, high in computation complexity and poor in real-time performance. The indoor three-dimensional scene rebuilding method based on the double-layer rectification method comprises Kinect calibration, SURF feature point extraction and matching, mapping from a feature point pair to a three-dimensional space point pair, three dimensional space point double-layer rectification based on random sample consensus (RANSAC) and inductively coupled plasma (ICP) methods and scene updating. According to the indoor three-dimensional scene rebuilding method based on the double-layer rectification method, the Kinect is adopted to obtain environmental data, and the double-layer rectification method is provided based on the RANSAC and the ICP. Indoor three-dimensional scene rebuilding which is economical and rapid is achieved, and the real-time performance of rebuilding algorithm and the rebuilding precision are effectively improved. The indoor three-dimensional scene rebuilding method based on the double-layer rectification method is applicable to the service robot field and other computer vision fields which are relative to the three-dimensional scene rebuilding.

A method and system for converting low-dose tomosynthesis projection images or reconstructed slices images with noise into higher quality, less noise, higher-dose-like tomosynthesis reconstructed slices, using of a trainable nonlinear regression (TNR) model with a patch-input-pixel-output scheme called a pixel-based TNR (PTNR). An image patch is extracted from an input raw projection views (images) of a breast acquired at a reduced x-ray radiation dose (lower-dose), and pixel values in the patch are entered into the PTNR as input. The output of the PTNR is a single pixel that corresponds to a center pixel of the input image patch. The PTNR is trained with matched pairs of raw projection views (images together with corresponding desired x-ray radiation dose raw projection views (images) (higher-dose). Through the training, the PTNR learns to convert low-dose raw projection images to high-dose-like raw projection images. Once trained, the trained PTNR does not require the higher-dose raw projection images anymore. When a new reduced x-ray radiation dose (low dose) raw projection images is entered, the trained PTNR outputs a pixel value similar to its desired pixel value, in other words, it outputs high-dose-like raw projection images where noise and artifacts due to low radiation dose are substantially reduced, i.e., a higher image quality. Then, from the “high-dose-like” projection views (images), “high-dose-like” 3D tomosynthesis slices are reconstructed by using a tomosynthesis reconstruction algorithm. With the “virtual high-dose” tomosynthesis reconstruction slices, the detectability of lesions and clinically important findings such as masses and microcalcifications can be improved.

The present discussion relates to the use of deep learning techniques to accelerate iterative reconstruction of images, such as CT, PET, and MR images. The present approach utilizes deep learning techniques so as to provide a better initialization to one or more steps of the numerical iterative reconstruction algorithm by learning a trajectory of convergence from estimates at different convergence status so that it can reach the maximum or minimum of a cost function faster.

The present invention provides a computer system and user interface that allows a user to readily view and analyze two-dimensional and three-dimensional in vivo images and imaging data. The user interface is well-suited for one or more of the following actions pertinent to in vivo light imaging: investigation and control of three-dimensional imaging data and reconstruction algorithms; control of topographic reconstruction algorithms; tomographic spectral imaging and analysis; and comparison of two-dimensional or three-dimensional imaging data obtained at different times.

The invention relates to an unmanned aerial vehicle aerial photography sequence image-based slope three-dimension reconstruction method. The method includes the following steps that: feature region matching and feature point pair extraction are performed on un-calibrated unmanned aerial vehicle multi-view aerial photography sequence images through adopting a feature matching-based algorithm; the geometric structure of a slope and the motion parameters of a camera are calculated through adopting bundle adjustment structure from motion and based on disorder matching feature points, and therefore, a sparse slope three-dimensional point cloud model can be obtained; the sparse slope three-dimensional point cloud model is processed through adopting a patch-based multi-view stereo vision algorithm, so that the sparse slope three-dimensional point cloud model can be diffused to a dense slope three-dimensional point cloud model; and the surface mesh of the slope is reconstructed through adopting Poisson reconstruction algorithm, and the texture information of the surface of the slop is mapped onto a mesh model, and therefore, a vivid three-dimensional slope model with high resolution can be constructed. The unmanned aerial vehicle aerial photography sequence image-based slope three-dimension reconstruction method of the invention has the advantages of low cost, flexibility, portability, high imaging resolution, short operating period, suitability for survey of high-risk areas and the like. With the method adopted, the application of low-altitude photogrammetry and computer vision technology to the geological engineering disaster prevention and reduction field can be greatly prompted.

The invention relates to a three-dimensional reconstruction algorithm introducing an interactive operation for a user, belonging to the technical field of a computer multimedia. The method is as followings: the user utilizes a plurality of cameras to obtain a two-dimensional image Ii of a plurality of viewpoints of an object and extracts a contour map of the object; the computer obtains a visual shell model of a real scene according to a geometric parameter of every camera and the contour map, and turns the visual shell model into a point cloud form; a two-dimensional characteristic in the image is extracted to optimize a part of a real surface model corresponding to the characteristics; the user divides the image Ii into a region of a smoothness and the region of a subsidence; a nonuniform weighted graph is set up according to the areas selected above to find out a minimal cut of the image to obtain the optimized scene surface model. Combined with an auxiliary operation of the user, the three-dimensional reconstruction algorithm is capable of reconstructing the high-quality three-dimensional model of the object relatively fast according to the multi-view image which is shot of the actual object and the camera parameter corresponding to each image.

A method for imaging objects in a highly scattering turbid medium comprises: using a group of sources and detectors to generate a plurality of emergent energy waves from the medium, determining the intensity data of the emergent energy waves and processing the intensity data by using an image reconstruction algorithm. Arrangement of sources-detectors may be in parallel (transmission and / or backscattering) geometry or in cylinder geometry. The reconstruction algorithm is a novel hybrid dual Fourier tomographic algorithm for a fast 3D image reconstruction. The forward models are the radiative transfer model based on the cumulant solution of the radiative transfer equation or the diffusion model based on the approximate diffusion equation.

Systems and methods are provided for reconstructing projection data that is mathematically complete or sufficient acquired using a computed tomography (CT) system. In one embodiment, a set of projection data representative of a sampled portion of a cylindrical surface is provided. The set of projection data is reconstructed using a suitable cone-beam reconstruction algorithm. In another embodiment, two or more sets of spatially interleaved helical projection data are processed using helical interpolation. The helically interpolated set of projection data is reconstructed using a two-dimensional axial reconstruction algorithm or a three-dimensional reconstruction algorithm.

The invention discloses a three-dimensional face reconstruction method which comprises the following steps of S1, positioning two-dimensional key points of a face image to be reconstructed; S2, positioning a three-dimensional key point coordinate in a three-dimensional model corresponding to the two-dimensional key points in the S1; S3, weighting-calculating shape reconstruction coefficients of a three-dimensional face and imaging model parameters by utilizing subunits of the key points in the S2; S4, synthesizing the shape of the three-dimensional face by utilizing subunits of a three-dimensional deformable model; and S5, extracting texture of the three-dimensional face by utilizing the imaging model and face symmetry. By means of the three-dimensional face reconstruction method, good reconstruction results of face images in any postures can be obtained, the computing is fast, and nonlinear optimization can converge quickly. Compared with the dense reconstruction algorithm in the prior art, the speed is improved by more than one order of magnitudes, and the performance is stable.

The invention provides a rapid three-dimensional reconstruction method based on light field digit refocusing. The method includes the following steps: firstly, a light field data obtaining device obtains space four-dimensional light field data; secondly, a digit refocusing module conducts digit refocusing processing on the space four-dimensional light field data to obtain a focusing plane sequence image; finally, a three-dimensional reconstruction module conducts three-dimensional reconstruction on the focusing plane sequence image. The invention further provides a rapid three-dimensional reconstruction system based on the light field digit refocusing. The rapid three-dimensional reconstruction system comprises the light field data obtaining device, the digit refocusing module and the three-dimensional reconstruction module. By means of the rapid three-dimensional reconstruction method and system, shooting is only needed one time, a camera and a target do not need to be moved, and results can be checked at any visual angle; the shooting difficulty and the reconstruction algorithm complexity are reduced, the image obtaining time is shortened, the method and system are suitable for three-dimensional reconstruction of the motion target, the application depth scope of a DFF algorithm is expanded, and the method and system are suitable for three-dimensional reconstruction of large-field-depth scenes.

Certain embodiments of the present invention provide a method for performing tomosynthesis including: receiving an image representative of an anatomy of a patient; allowing an interaction with the image to arrange at least one element with respect to the image to form an arrangement; and prescribing at least one parameter for obtaining a tomosynthesis image based at least in part on the arrangement. In an embodiment, the method further includes performing tomosynthesis in accordance with the at least one parameter. In an embodiment, the at least one element includes a detector representation. In an embodiment, the at least one element includes at least one thickness guide. In an embodiment, the at least one element includes at least one slice location guide. In an embodiment, the at least one parameter includes at least one of: a detector position, a detector size, a thickness size, a thickness position, a slice size, a slice position, a slice thickness, a slice separation, a field of view, a reconstruction algorithm, a hanging protocol, and an image processing routine. In an embodiment, the at least one parameter includes at least one of: an x-ray source location, an x-ray source angulation, an x-ray beam intensity, an x-ray beam gating, and a detector sensitivity.

The invention discloses a dual-wavelength binocular vision seam tracking method. The method comprises the steps including image acquisition, data processing, seam tracking and the like. The invention further discloses a tracking system for implementing the method. The system adopts a near-infrared and structured light dual-wavelength binocular vision sensing system, images of a molten pool and different wavelengths of seam area images with of seams are measured simultaneously and transmitted to a miniature industrial control computer, and the seam positions are measured accurately with a multi-information fusion algorithm and a seam image three-dimensional reconstruction algorithm; the miniature industrial control computer adopts the Kalman filter algorithm to perform optimal estimation on the seam tracking deviation state according to a seam position detection result, a servo driver drives a servo motor to move so as to control a 3-axis motion workbench to generate corresponding motion, a welding torch or a laser head is controlled for deviation correction, and the seams are tracked accurately. The system can eliminate hard light, splashing and electromagnetic interference on a welding site and improve the seam tracking accuracy and reliability.

The invention provides a method for constructing a surgical virtual operation teaching and training system. The method comprises the following concrete steps: (1) acquiring various inspection data classified according to normal people and patients, intensively storing the acquired data, and constructing an integrated male virtual human model and an integrated female virtual human model; (2) carrying out geometric modeling, computational modeling and deformation computation on medical data, and carrying out modeling on bones and soft tissues by adopting a multi-outline three-dimensional reconstruction algorithm; (3) reconstructing by adopting a three-dimensional model of 3DMAX10, mapping and giving physiological characteristics to organic tissues; (4) compiling related objects and simulated scenes of a virtual operation by virtual reality modeling language (VRML); (5) carrying out preoperative preparation in the virtual operation scenes, and checking and confirming patient information; (6) carrying out complete operational details of the actual method of the virtual operation again; (7) establishing a simulated operation teaching evaluation system; and (8) carrying out comprehensive evaluation and examination on a teacher and each trainee. In the method, the simulated operation teaching system is constructed by utilizing the virtual reality technology, thereby providing a wide and transparent simulated teaching and research platform for hospitals and medical schools.