RFA Guardian: Comprehensive Simulation of Radiofrequency Ablation Treatment of Liver Tumors

The RFA Guardian is a comprehensive application for high-performance patient-specific simulation of radiofrequency ablation of liver tumors. We address a wide range of usage scenarios. These include pre-interventional planning, sampling of the parameter space for uncertainty estimation, treatment evaluation and, in the worst case, failure analysis. The RFA Guardian is the first of its kind that exhibits sufficient performance for simulating treatment outcomes during the intervention. We achieve this by combining a large number of high-performance image processing, biomechanical simulation and visualization techniques into a generalized technical workflow. Further, we wrap the feature set into a single, integrated application, which exploits all available resources of standard consumer hardware, including massively parallel computing on graphics processing units. This allows us to predict or reproduce treatment outcomes on a single personal computer with high computational performance and high accuracy. The resulting low demand for infrastructure enables easy and cost-efficient integration into the clinical routine. We present a number of evaluation cases from the clinical practice where users performed the whole technical workflow from patient-specific modeling to final validation and highlight the opportunities arising from our fast, accurate prediction techniques

Garcinoxanthones from Garcinia mangostana L. against SARS-CoV-2 infection and cytokine storm pathway inhibition: A viroinformatics study

Context: Mangosteen (Garcinia mangostana L.) is used in traditional medicine as an antibacterial, antioxidant, and anti-inflammatory. Aims: To determine the molecular mechanism and potential of garciniaxanthone derivate compounds from G. mangostana as SARS-CoV-2 antiviral and prevent cytokine storm through in silico approach. Methods: Ligand and protein samples were obtained from databases such as PubChem and Protein Databank, then drug-likeness analysis using Lipinski, Ghose, Veber, Egan, and Muege rules on SwissADME server, prediction of antiviral probability through PASSOnline server. Furthermore, molecular docking simulation with PyRx v1.0 software (Scripps Research, USA) with an academic license, identification of interactions and chemical bond positions of ligands on the target by PoseView server, 3D visualization of PyMOLv.2.5.2 software (Schrödinger, Inc., USA) with an academic license, molecular dynamics simulation for molecular stability prediction by CABS-flex v2.0 server, target prediction of antiviral candidate compounds by SwissTargetPrediction server, pathway analysis through STRING v11.5 database, and toxicity by ProTox-II server were used. Results: Garciniaxanthone C from G. mangostana was found to be a drug-like molecule with low toxicity. This can be a candidate for SARS-Cov-2 antiviral through inhibitor activity on two viral enzymes consisting of Mpro and replicase with a binding affinity value that is more negative than other garciniaxanthone derivates and is stable. Garciniaxanthone C is predicted to bind and inhibit pro-inflammatory proteins that trigger cytokine storms, such as NFKB1 and PTGS2. Conclusions: Garciniaxanthone derivative compounds from G. mangostana may be candidates for SARS-CoV-2 antiviral and preventing cytokine storm through garciniaxanthone C activity

Lecture Notes in Computer Science 1 Calibration Update Technique for a Zoom Lens

Abstract. A technique for a zoom lens camera is presented that enable to update continuously camera intrinsic parameters while zooming. This is based on the fact that the spatial angle subtended by the optical center and the same two 3-D points in the standard camera coordinate system remains invariant for subsequent image frames on which the two 3-D points are located. The new focal length value is obtained as the solution of the quadratic equation we derive from the angular invariance. We give an error estimate to show how the uncertainty in the localization of corresponding points in the image frames may affect the accuracy of the updated value of the focal length. We report the results of two experiments when sequences of magnified images were taken by fixed and by rotating camera. 1

Direct Recovery of the Camera Internal Parameters Using Known Angles

We address the problem of direct internal calibration of a camera from a set of known angles between optical rays. A pen-size laser crosshair projector is used to generate a reference pattern whose angular features are known. Each known angle between a pair of optical rays imposes one angular constraint on the internal camera parameters. Several constraints form a system of equations, which is solved for the internal parameters. Because the angular constraints are given in the standard coordinate system of the camera, the internal parameters are recovered directly, that is without referring to any world coordinate system. An advantage that follows, is that calibration does not require precise measurements of 3-D coordinates of reference points. The final calibration parameters as well as the first order radial distortion parameter are computed by nonlinear optimization. We analyze an accuracy of angular values between optical rays and present experimental results of camera calibration. Angular calibration is fast, robust and easy to implement method, which is suitable for quick “offlab” calibration of cameras. 1

Header for SPIE use View-based Method for Relative Orientation in the Pipe 1

The paper addresses the navigation problem for an autonomous robot designed to inspect sewerage. The robot, which is about half size of the sewer diameter, must keep its orientation in the entirely dark sewerage. The only a priory information known is the geometrical shape of the sewer (cylindrical, etc). This implies a strong geometrical constraint on the environment the robot can expect. In the paper we worked out an active vision system to be used on-board of the sewer robot. The system has two components: (a) an optical camera and (b) a laser crosshair projector generating an ideal cross. The print (“the cross-trace”) left by the laser crosshair projector on the pipe surface is snapped with the camera. The image of the “cross-trace ” on the camera plane is two intersecting quadratic curves. The shape of the curves gives a clue (up to the symmetry of the sewer) about a direction the robot looks. In this paper we investigate the curves that are the images of the laser “cross-traces ” as they are seen on the camera plane for a simulated environmental model. We show how the shape of the curves viewed by the camera depends upon particular camera/laser relative position and orientation, assuming a cylindrical sewer pipe. We give a strategy how to align the robot with the sewer axis on the basis of curve images

Using Angles for Internal Camera Calibration

Standard camera calibration technique is based on the relationship between the 3D point coordinates in the object space and their respective 2D coordinates in the image plane. Thus precise distance measurements for a set of reference points is the necessary burden of the calibration procedure. Nevertheless camera projective mapping is irreversible process: whereas a set of six reference points uniquely defines the camera parameters their precise position can not be retrieved on the basis of a single image. The image will not change as long as the 3D position of the reference point varies along its optical ray tended by the respective image point and the camera optical center. It follows that a set of such "reference rays" uniquely defines camera model. The idea presented in the paper is to perform internal camera calibration using angular information for a set of reference points as they are seen in the image plane. We call this approach angular calibration. We use a spe..

Automatic restoration of space characteristics of stage on stereoscopic pair of images

The digital representation of a stereoscopic pair of images is investigated in the paper aiming at the creation of a quick automatiu algorithm of the restoration of the stage three-dimensionad form of a stereoscopic pair of images. During the investigation the mathematical modelling of stereopsis, the numerical modelling of the stereoreconstruction process on the base of personal computers and transputer network have been used. As a result methods of the account of a priori information about a stage have been developed as well as new methods of the indication of correcsonding signs on stereo pair images, methods of the videodata pyramidal structure use and the new algorthm of the automatic registration of a stereoscopic pair on this base. The algorithm serviceability has been investigated experimentally on various stereo images. The algorithm program realization in the transputer system makes it possible to hold the restoration of the stage three-dimensional form in real time. The paper resluts may find their field of application in cartography, construction of three-dimensional form of celestial bodies, mine surveyings, systems of technical vision of autonomous devicesAvailable from VNTIC / VNTIC - Scientific & Technical Information Centre of RussiaSIGLERURussian Federatio

Neural object recognition by hierarchical learning and extraction of essential shapes

Abstract. We present a hierarchical system for object recognition that models neural mechanisms of visual processing identified in the mammalian ventral stream. The system is composed of neural units organized in a hierarchy of layers with increasing complexity. A key feature of the system is that the neural units learn their preferred patterns from visual input alone. Through this “soft wiring ” of neural units the system becomes tuned for target object classes through pure visual experience and with no prior labeling. Object labels are only introduced to train a classifier on the system’s output. The system’s tuning takes place in a feedforward path. We also present a neural mechanism for back projection of the learned image patterns down the hierarchical layers. This feedback mechanism could serve as a starting point for integration of what- and where-information processed by the ventral and dorsal stream. We test the neural system with natural images from publicly available datasets of natural scenes and handwritten digits.