Update Course and Advanced Techniques in MNPS (version 10.36.07, 2019-2020). . Virtual Fiducials Mode
Translation into English of the original Portuguese version.
MNPS is developed by Mevis Informática Médica, São Paulo, Brazil
Update Course and Advanced Techniques in MNPS (version 10.36.07, 2019-2020). Functional Neurosurgery Planning
Translation into English of the original Portuguese version.
MNPS is developed by Mevis Informática Médica, São Paulo, Brazil
Overview of Mevis Neurosurgery Planning System (MNPS). MNPS allows pre-planning and simulation of several stereotactic neurosurgery procedures. MNPS is a software only system. It has support for most stereotactic apparatus on the market. Stereotactic coordinates computation, image registration and fusion, functional neurosurgery tools, tractography from DTI, radiosurgery and more. Modeling of DBS geometry, for several brands and models. MNPS has correction and whole support for ring tilt inside CT gantry for all stereotactic models. The present MNPS was born in 1989 as "NSPS" and "MSPS" was its second name. Some bibliography referring the use of NSPS/MSPS/MNPS is presented at the end. It is a Windows based system. Must be used on computers with Intel CPUs due to compilation issues. NVidia graphic processors are recommended. Allows use on notebooks and surface computers, needs at less a free USB port.
Basic tutorial to start a Stereotactic pre-surgery plan with MNPS. Includes loading of stereotactic CTs and registration with non-stereotactic MRIs. Does not cover advanced topics like functional maps, DBS simulations, 3D rendering, Radiosurgery o Brachytherapy.
Search for other presentations covering advanced topics.
This version of the document corresponds to MNPS version 10.33.04
MNPS is an Stereotactic Planning System, for Windows PCs developed by "MEVIS Informática Médica LTDA"l.
MNPS is a stereotactic planning and post-op evaluation system developed by Mevis Informatica Médica LTDA. Support for biopsy, functional neurosurgery, DBS, VTA, X-ray stereotactic localization, 2D-3D registration, image fusion, tractography, sEEG, and much more. Versions for a lot of frames manufactures and models; FiMe, Micromar, Bramsys, Leksell, CRW, BRW, ZD, Macom, Riechert-Mundiguer, Adeor-Zeppelin, EstereoFlex.
DBS support: Medtronic, St.Jude-Abbott, Boston Sc. and SceneRay. Isotropic and directional DBS
StereoCheck, StereoCheckRM, and CheckBRW - Stereotactic Coordinates VerificationArmando Alaminos Bouza
StereoCheck is an APP for independent verification of Stereotactic Coordinates on Neurosurgery. It is available on Apple "App Store". It can be installed on iPhone or iPad.
StereoCheck has support for most stereotactic apparatus on the market, including
FiMe, Bramsys, Macom, CRW, Leksell, ZD and Riechert-Mundinger.
There are special versions of the application for the BRW and Riechert-Mundinger apparatus.
Developed by Mevis Informática Médica LTDA.
Disparity map generation based on trapezoidal camera architecture for multi v...ijma
Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities,
the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video
remains a huge challenge. This paper presents the mathematical description of trapezoidal camera
architecture and relationships which facilitate the determination of camera position for visual content
acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera
Architecture is that it allows for adaptive camera topology by which points within the scene, especially the
occluded ones can be optically and geometrically viewed from several different viewpoints either on the
edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and
the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate
description could very well be used to address the issue of occlusion which continues to be a major
problem in computer vision with regards to the generation of depth map.
Update Course and Advanced Techniques in MNPS (version 10.36.07, 2019-2020). Functional Neurosurgery Planning
Translation into English of the original Portuguese version.
MNPS is developed by Mevis Informática Médica, São Paulo, Brazil
Overview of Mevis Neurosurgery Planning System (MNPS). MNPS allows pre-planning and simulation of several stereotactic neurosurgery procedures. MNPS is a software only system. It has support for most stereotactic apparatus on the market. Stereotactic coordinates computation, image registration and fusion, functional neurosurgery tools, tractography from DTI, radiosurgery and more. Modeling of DBS geometry, for several brands and models. MNPS has correction and whole support for ring tilt inside CT gantry for all stereotactic models. The present MNPS was born in 1989 as "NSPS" and "MSPS" was its second name. Some bibliography referring the use of NSPS/MSPS/MNPS is presented at the end. It is a Windows based system. Must be used on computers with Intel CPUs due to compilation issues. NVidia graphic processors are recommended. Allows use on notebooks and surface computers, needs at less a free USB port.
Basic tutorial to start a Stereotactic pre-surgery plan with MNPS. Includes loading of stereotactic CTs and registration with non-stereotactic MRIs. Does not cover advanced topics like functional maps, DBS simulations, 3D rendering, Radiosurgery o Brachytherapy.
Search for other presentations covering advanced topics.
This version of the document corresponds to MNPS version 10.33.04
MNPS is an Stereotactic Planning System, for Windows PCs developed by "MEVIS Informática Médica LTDA"l.
MNPS is a stereotactic planning and post-op evaluation system developed by Mevis Informatica Médica LTDA. Support for biopsy, functional neurosurgery, DBS, VTA, X-ray stereotactic localization, 2D-3D registration, image fusion, tractography, sEEG, and much more. Versions for a lot of frames manufactures and models; FiMe, Micromar, Bramsys, Leksell, CRW, BRW, ZD, Macom, Riechert-Mundiguer, Adeor-Zeppelin, EstereoFlex.
DBS support: Medtronic, St.Jude-Abbott, Boston Sc. and SceneRay. Isotropic and directional DBS
StereoCheck, StereoCheckRM, and CheckBRW - Stereotactic Coordinates VerificationArmando Alaminos Bouza
StereoCheck is an APP for independent verification of Stereotactic Coordinates on Neurosurgery. It is available on Apple "App Store". It can be installed on iPhone or iPad.
StereoCheck has support for most stereotactic apparatus on the market, including
FiMe, Bramsys, Macom, CRW, Leksell, ZD and Riechert-Mundinger.
There are special versions of the application for the BRW and Riechert-Mundinger apparatus.
Developed by Mevis Informática Médica LTDA.
Disparity map generation based on trapezoidal camera architecture for multi v...ijma
Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities,
the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video
remains a huge challenge. This paper presents the mathematical description of trapezoidal camera
architecture and relationships which facilitate the determination of camera position for visual content
acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera
Architecture is that it allows for adaptive camera topology by which points within the scene, especially the
occluded ones can be optically and geometrically viewed from several different viewpoints either on the
edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and
the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate
description could very well be used to address the issue of occlusion which continues to be a major
problem in computer vision with regards to the generation of depth map.
Face recognition across non uniform motionjpstudcorner
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
Conventional non-vision based navigation systems relying on purely Global Positioning System (GPS) or inertial sensors can provide the 3D position or orientation of the user. However GPS is often not available in forested regions and cannot be used indoors. Visual odometry provides an independent method to estimate position and orientation of the user/system based on the images captured by the moving user accurately. Vision based systems also provide information (e.g. images, 3D location of landmarks, detection of scene objects) about the scene that the user is looking at. In this project, a set of techniques are used for the accurate pose and position estimation of the moving vehicle for autonomous navigation using the images obtained from two cameras placed at two different locations of the same area on the top of the vehicle. These cases are referred to as stereo vision. Stereo vision provides a method for the 3D reconstruction of the environment which is required for pose and position estimation. Firstly, a set of images are captured. The Harris corner detector is utilized to automatically extract a set of feature points from the images and then feature matching is done using correlation based matching. Triangulation is applied on feature points to find the 3D co-ordinates. Next, a new set of images is captured. Then repeat the same technique for the new set of images too. Finally, by using the 3D feature points, obtained from the first set of images and the new set of images, the pose and position estimation of moving vehicle is done using QUEST algorithm.
Intelligent indoor mobile robot navigation using stereo visionsipij
Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar
sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a
map of the corresponding environment. Stereo vision,while still being a rapidly developing technique in the
field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This
paper aims at describing an experimental approach for the building of a stereo vision system that helps the
robots to avoid obstacles and navigate through indoor environments and at the same time remaining very
much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors
which helps in the successful navigation through different types of complex environments. The data from
the sensor enables the robot to create the two dimensional topological map of unknown environments and
stereo vision systems models the three dimension model of the same environment.
In this paper the process of 3D modelling from video is presented. Analysed previous research related to
this process, and specifically described algorithms for detecting and matching key points. We described
their advantages and disadvantages, and made a critical analysis of algorithms. In this paper, the three
detectors (SUSAN, Plessey and Förstner) are tested and compare. We used video taken with hand held
camera of a cube and compare these detectors on it (taking into account their parameters of accuracy and
repeatability). In conclusion, we practically made 3D model of the cube from video used these detectors in
the first step of the process and three algorithms (RANSAC, MSAC and MLESAC) for matching data.
Tracking Chessboard Corners Using Projective Transformation for Augmented Rea...CSCJournals
Augmented reality has been a topic of intense research for several years for many applications. It consists of inserting a virtual object into a real scene. The virtual object must be accurately positioned in a desired place. Some measurements (calibration) are thus required and a set of correspondences between points on the calibration target and the camera images must be found. In this paper, we present a tracking technique based on both detection of Chessboard corners and a least squares method; the objective is to estimate the perspective transformation matrix for the current view of the camera. This technique does not require any information or computation of the camera parameters; it can used in real time without any initialization and the user can change the camera focal without any fear of losing alignment between real and virtual object.
Adaptive Disparity Estimation for Auto Convergence of Region of Interest in a...ijcga
Recently, various devices for three-dimensional (3-D) effect have been developed. For producing 3-D effect of the scene or the region of interest (ROI), disparity should be accurately estimated. People watching 3-D video feel visual fatigue if magnitude of parallax for the ROI is excessively large because a convergence point is not accurately put on the ROI. For producing 3-D effect, a 3-D formatter overlaps left and right images by shifting horizontally the right image by the estimated disparity of the ROI. In this paper, an adaptive disparity estimation algorithm for auto convergence of the ROI in a video is proposed using the first-order Taylor series expansion of disparity and adaptive disparity search range prediction in a stereoscopic video. First, a stereo video that consists of a number of pairs of left and right images is captured in parallel stereo camera configuration. A window in each frame is selected within the ROI and tracked. Then, for automatically adjusting a convergence point on the ROI, two steps are needed with the previously estimated disparities. The first-order Taylor series expansion is used to approximate disparity of the current frame of a video. Then, a moving average filter is used to adaptively determine disparity search range in similarity measure computation. Subjective evaluation such as visual fatigue, comfort, and 3-D effect of the proposed algorithm and existing algorithms is performed. Experimental results with four test videos and subjective evaluation show that the proposed algorithm gives 3-D effect with visual comfort.
Overview of Mevis Neurosurgery Planning System (MNPS). MNPS allows pre-planning and simulation of several stereotactic neurosurgery procedures. MNPS is a software-only system. It has support for most stereotactic apparatus on the market. Stereotactic coordinates computation, image registration, and fusion, functional neurosurgery tools, tractography from DTI, radiosurgery and more. Modeling of DBS geometry, for several brands and models and FEM for electric fields and VTA. MNPS has the correction and whole support for ring tilt inside CT gantry for all stereotactic models. The present MNPS was born in 1989 as "NSPS" and "MSPS" was its second name. Some bibliography referring the use of NSPS/MSPS/MNPS is presented at the end. It is a Windows-based system. Must be used on computers with Intel CPUs due to compilation issues. NVidia graphics processors are recommended. Allows use of notebooks and surface computers, needs at less a free USB port.
MNPS is a Stereotactic pre-planning and post-planning system.
Suport for several stereotactic apparatus. Image Registration and Fusion. Image Segmentation. DWI, DTI, FA and Tractography support. DBS Electric Field and VTA representation.
MNPS is a stereotactic planning and post-op evaluation system developed by Mevis Informatica Médica LTDA. Support for biopsy, functional neurosurgery, DBS, VTA, X-ray stereotactic localization, 2D-3D registration, image fusion, tractography and much more. Versions for a lot of frames manufactures and models; FiMe, Micromar, Bramsys, Leksell, CRW, BRW, ZD, Macom, Riechert-Mundiguer, Adeor-Zeppelin, EstereoFlex.
DBS support: Medtronic, St.Jude-Abbott, Boston Sc. and SceneRay.
Learn more: https://www.brainlab.com/spinal-navigation
Brainlab Spinal Navigation combines state-of-the-art touch screen based image control with best-in-class registration methods for image-guided surgery. As an open navigation platform, Brainlab Spinal Navigation enables accurate pedicle screw placement as well as drastic reduction of X-Ray exposure to both the surgical team and the patient. Navigation of implants and instruments is possible in 2D images, 3D fluoroscopy scans, MR or CT datasets in all stages of surgery—from incision planning to implant placement.
Visual Mapping and Collision Avoidance Dynamic Environments in Dynamic Enviro...Darius Burschka
How conventional vision is more appropriate for control since it provides also error analysis. There is a lot of information in the images that is lost when converting to 3D
Face recognition across non uniform motionjpstudcorner
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
Conventional non-vision based navigation systems relying on purely Global Positioning System (GPS) or inertial sensors can provide the 3D position or orientation of the user. However GPS is often not available in forested regions and cannot be used indoors. Visual odometry provides an independent method to estimate position and orientation of the user/system based on the images captured by the moving user accurately. Vision based systems also provide information (e.g. images, 3D location of landmarks, detection of scene objects) about the scene that the user is looking at. In this project, a set of techniques are used for the accurate pose and position estimation of the moving vehicle for autonomous navigation using the images obtained from two cameras placed at two different locations of the same area on the top of the vehicle. These cases are referred to as stereo vision. Stereo vision provides a method for the 3D reconstruction of the environment which is required for pose and position estimation. Firstly, a set of images are captured. The Harris corner detector is utilized to automatically extract a set of feature points from the images and then feature matching is done using correlation based matching. Triangulation is applied on feature points to find the 3D co-ordinates. Next, a new set of images is captured. Then repeat the same technique for the new set of images too. Finally, by using the 3D feature points, obtained from the first set of images and the new set of images, the pose and position estimation of moving vehicle is done using QUEST algorithm.
Intelligent indoor mobile robot navigation using stereo visionsipij
Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar
sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a
map of the corresponding environment. Stereo vision,while still being a rapidly developing technique in the
field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This
paper aims at describing an experimental approach for the building of a stereo vision system that helps the
robots to avoid obstacles and navigate through indoor environments and at the same time remaining very
much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors
which helps in the successful navigation through different types of complex environments. The data from
the sensor enables the robot to create the two dimensional topological map of unknown environments and
stereo vision systems models the three dimension model of the same environment.
In this paper the process of 3D modelling from video is presented. Analysed previous research related to
this process, and specifically described algorithms for detecting and matching key points. We described
their advantages and disadvantages, and made a critical analysis of algorithms. In this paper, the three
detectors (SUSAN, Plessey and Förstner) are tested and compare. We used video taken with hand held
camera of a cube and compare these detectors on it (taking into account their parameters of accuracy and
repeatability). In conclusion, we practically made 3D model of the cube from video used these detectors in
the first step of the process and three algorithms (RANSAC, MSAC and MLESAC) for matching data.
Tracking Chessboard Corners Using Projective Transformation for Augmented Rea...CSCJournals
Augmented reality has been a topic of intense research for several years for many applications. It consists of inserting a virtual object into a real scene. The virtual object must be accurately positioned in a desired place. Some measurements (calibration) are thus required and a set of correspondences between points on the calibration target and the camera images must be found. In this paper, we present a tracking technique based on both detection of Chessboard corners and a least squares method; the objective is to estimate the perspective transformation matrix for the current view of the camera. This technique does not require any information or computation of the camera parameters; it can used in real time without any initialization and the user can change the camera focal without any fear of losing alignment between real and virtual object.
Adaptive Disparity Estimation for Auto Convergence of Region of Interest in a...ijcga
Recently, various devices for three-dimensional (3-D) effect have been developed. For producing 3-D effect of the scene or the region of interest (ROI), disparity should be accurately estimated. People watching 3-D video feel visual fatigue if magnitude of parallax for the ROI is excessively large because a convergence point is not accurately put on the ROI. For producing 3-D effect, a 3-D formatter overlaps left and right images by shifting horizontally the right image by the estimated disparity of the ROI. In this paper, an adaptive disparity estimation algorithm for auto convergence of the ROI in a video is proposed using the first-order Taylor series expansion of disparity and adaptive disparity search range prediction in a stereoscopic video. First, a stereo video that consists of a number of pairs of left and right images is captured in parallel stereo camera configuration. A window in each frame is selected within the ROI and tracked. Then, for automatically adjusting a convergence point on the ROI, two steps are needed with the previously estimated disparities. The first-order Taylor series expansion is used to approximate disparity of the current frame of a video. Then, a moving average filter is used to adaptively determine disparity search range in similarity measure computation. Subjective evaluation such as visual fatigue, comfort, and 3-D effect of the proposed algorithm and existing algorithms is performed. Experimental results with four test videos and subjective evaluation show that the proposed algorithm gives 3-D effect with visual comfort.
Overview of Mevis Neurosurgery Planning System (MNPS). MNPS allows pre-planning and simulation of several stereotactic neurosurgery procedures. MNPS is a software-only system. It has support for most stereotactic apparatus on the market. Stereotactic coordinates computation, image registration, and fusion, functional neurosurgery tools, tractography from DTI, radiosurgery and more. Modeling of DBS geometry, for several brands and models and FEM for electric fields and VTA. MNPS has the correction and whole support for ring tilt inside CT gantry for all stereotactic models. The present MNPS was born in 1989 as "NSPS" and "MSPS" was its second name. Some bibliography referring the use of NSPS/MSPS/MNPS is presented at the end. It is a Windows-based system. Must be used on computers with Intel CPUs due to compilation issues. NVidia graphics processors are recommended. Allows use of notebooks and surface computers, needs at less a free USB port.
MNPS is a Stereotactic pre-planning and post-planning system.
Suport for several stereotactic apparatus. Image Registration and Fusion. Image Segmentation. DWI, DTI, FA and Tractography support. DBS Electric Field and VTA representation.
MNPS is a stereotactic planning and post-op evaluation system developed by Mevis Informatica Médica LTDA. Support for biopsy, functional neurosurgery, DBS, VTA, X-ray stereotactic localization, 2D-3D registration, image fusion, tractography and much more. Versions for a lot of frames manufactures and models; FiMe, Micromar, Bramsys, Leksell, CRW, BRW, ZD, Macom, Riechert-Mundiguer, Adeor-Zeppelin, EstereoFlex.
DBS support: Medtronic, St.Jude-Abbott, Boston Sc. and SceneRay.
Learn more: https://www.brainlab.com/spinal-navigation
Brainlab Spinal Navigation combines state-of-the-art touch screen based image control with best-in-class registration methods for image-guided surgery. As an open navigation platform, Brainlab Spinal Navigation enables accurate pedicle screw placement as well as drastic reduction of X-Ray exposure to both the surgical team and the patient. Navigation of implants and instruments is possible in 2D images, 3D fluoroscopy scans, MR or CT datasets in all stages of surgery—from incision planning to implant placement.
Visual Mapping and Collision Avoidance Dynamic Environments in Dynamic Enviro...Darius Burschka
How conventional vision is more appropriate for control since it provides also error analysis. There is a lot of information in the images that is lost when converting to 3D
leewayhertz.com-HOW IS A VISION TRANSFORMER MODEL ViT BUILT AND IMPLEMENTED.pdfrobertsamuel23
Recent years have seen deep learning completely transform computer vision and image
processing. Convolutional neural networks (CNNs) have been the driving force behind
this transformation due to their ability to efficiently process large amounts of data,
enabling the extraction of even the smallest image features.
MNPS. Update Course and Advanced Techniques. Segmentation and ROIs.Armando Alaminos Bouza
Update Course and Advanced Techniques in MNPS (version 10.36.07, 2019-2020). Segmentation tools and Region Of Interest (ROI)
Translation into English of the original Portuguese version.
MNPS is developed by Mevis Informática Médica, São Paulo, Brazil
MNPS, resumo das novidades de 2017 até 2018.
MNPS é um sistema de planejamento de neurocirurgia estereotáxica.
MNPS is stereotactic Planning System developed by Mevis Informatica Médica, Brazil
arivis Vision4D - IMAGE ANALYSIS WHICH FITS YOUR DATA (2 pages, 2020)Johannes Amon
arivis Vision4D is the leading software for exploring and analysing large multi-dimensional image datasets created by confocal, Light Sheet, Multi-Photon or Electron Microscopy. arivis Vision4D can handle several hundred Gigabytes or terabytes of such image data as easily as if they were just a few megabytes in size.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/mvtec/embedded-vision-training/videos/pages/may-2017-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Olaf Munkelt, Co-founder and Managing Director at MVTec Software GmbH, presents the "Embedded Vision Made Smart: Introduction to the HALCON Embedded Machine Vision Library" tutorial at the May 2017 Embedded Vision Summit.
In this presentation, Munkelt demonstrates how easy it is to develop an embedded vision (identification) application based on the HALCON Embedded standard software library and get it running on a Raspberry Pi. The demonstration showcases the benefits of HALCON Embedded for industrial applications. Munkelt presents how HALCON Embedded allows users to quickly develop a machine vision application on a standard PC and thereby eases programming of an embedded system and shortens development time. Viewers will learn about HALCON Embedded’s speed and robustness, and also how MVTec’s support team provides advice and services for users.
HALCON Embedded, derived from MVTec’s renowned HALCON industrial vision software library, is portable to various microprocessors/DSPs, operating systems, and compilers. Thus, HALCON Embedded is available for numerous smart cameras and other embedded systems and enables system integrators, OEMs and developers of embedded vision applications to bring the full power of HALCON to embedded devices. Users benefit from the most comprehensive machine vision library on the market running on their embedded platforms, reducing development cost and effort.
Contours Planning and Visual Servo Control of XXY Positioning System Using NU...journal ijrtem
ABSTRACT : This study aims to develop contours planning and visual servo control technologies for a XXY positioning stage for tracking the two-dimensional contours precisely. First, the two-dimensional contours are planned by using the non-uniform rational basis spline (NURBS) interpolation approach. Subsequently, the visual servo control mechanism, which involves five steps image processing procedures, is further designed to perform the closed-loop motion control for high-precision positioning performance. During the control process, the positioning error is monitored online. If the positioning error is larger than the pre-defined threshold, a compensation control will be executed immediately to compensate the inaccurate motions. In addition, a friendly human-machine interface (HMI), which can show the movement of the stage in real-time, is developed. Finally, the experimental results demonstrated the favorable positioning performance of the XXY positioning system for tracking the two-dimensional contours. Keywords: Image processing, NURBS, positioning control, XXY positioning stage
Brainlab Cranial Navigation. Efficiently combining decisive aspects of neurosurgery.
Brainlab® Cranial 3.0 provides a new user experience on Kick® and Curve™ navigation platforms. Fully
DICOM-based, cranial navigation and Brainlab Elements* can run parallel with instant synchronization
to update navigated image sets with new fusion results, SmartBrush® objects or trajectories.
Aspectos físicos para comisionamiento del TPS en la radiocirugía con colimado...Armando Alaminos Bouza
Charla en el:
1er Congreso Mundial Virtual de Radiocirugía y Radioterapia.
Septiembre / 2020
Aspectos físicos, dosimétricos y geométricos en el comisionamiento del sistema de planificación de radiocirugía estereotáxica.
Todas las presentaciones en youtube:
https://www.youtube.com/watch?time_continue=2518&v=eYQvKLtoth0&feature=emb_logo
CAT3D: Fitting the penumbra parameters of RSD for good reproduction of half b...Armando Alaminos Bouza
CAT3D: Optimization of penumbra parameters of RSD for good reproduction of half beam superpositions on CAT3D
CAT3D is radiotherapy planning system developed by Mevis Informática Médica LTDA. Brasil
CAT3D is a Therapy Planning System developed by Mevis Informática Médica, São Paulo, Brazil.
This document presents a short description in Spanish of the main algorithms used by CAT3D to model dose distributions.
Document by Armando Alaminos Bouza
MNPS is a stereotactic planning and post-planning system. Support for most commercial models and manufacturers of stereotactic apparatus. Image Registration and Fusion, Radiosurgery, functional atlas, tractography, etc.
MNPS is a stereotactic planning and post-planning system. Support for most commercial stereotactic models and manufacturers. Support for image registration and fusion, stereotactic atlases, DBS models, DBS electric fields, Radiosurgery and much more. Image segmentation.
MNPS is developed by MEVIS Informática Médica LTDA.
MNPS is a stereotactic planning and post-planning system. Support for most commercial stereotactic models and manufacturers. Support for image registration and fusion, stereotactic atlases, DBS models, DBS electric fields, Radiosurgery and much more. Image segmentation.
MNPS is developed by MEVIS Informática Médica LTDA.
MNPS is a stereotactic planning and post-planning system. Support for most commercial stereotactic models and manufacturers. Support for image registration and fusion, stereotactic atlases, DBS models, DBS electric fields, Radiosurgery and much more. Image segmentation.
MNPS is developed by MEVIS Informática Médica LTDA.
MNPS is a stereotactic planning and post-planning system. Support for most commercial stereotactic models and manufacturers. Support for image registration and fusion, stereotactic atlases, DBS models, DBS electric fields, Radiosurgery and much more. Image segmentation.
MNPS is developed by MEVIS Informática Médica LTDA.
MNPS is a stereotactic planning and post-planning system. Support for most commercial stereotactic models and manufacturers. Support for image registration and fusion, DBS models, DBS electric fields, Radiosurgery and much more. Image segmentation.
MNPS is developed by MEVIS Informática Médica LTDA.
MNPS is a stereotactic planning and post-planning system. Support for most commercial stereotactic models and manufacturers. Support for image registration and fusion, DBS models, DBS electric fields, Radiosurgery and much more. Image segmentation.
MNPS is developed by MEVIS Informática Médica LTDA.
MNPS is a stereotactic planning and post-planning system. Support for most commercial models and manufacturers of stereotactic apparatus. Image Registration and Fusion, Radiosurgery, functional atlas, etc.
Test case: Rosenbrock, Ackley, Restrigin, Bartels-Conn, Booth, and Bukin.N.6 functions.
Algorithms: SolvOpt, NEWUOA, Rosenbrock, Hill-Climbing, Gradient-Descent, Simulated-Anneal.
As the viewer cut columns, I recommend downloading the LibreOffice document.
Novidades do CAT3D para IMRT. Moduladores sólidos e Step and Shoot. Constrains, Other Healthy Tissue.
CAT3D is a TPS developed by Mevis Informática Médica, Brasil. For Windows 64bits PCs
Aborda temas como Total Body Irradiation, soma de dose em multiplas fases, exportar planos em Dicom RT, Lantis RTP-link, .mlc
Collapsed Cones Superposition and PencilBeam
CAT3D is a TPS develeped by Mevis Informática Médica LTDA, Brasil
Registro de imagens. Fusão de imagens, CT, MRI, PET, SPECT. Maximização de Informação Mútua. Mutual Information. DRR e Portal Check. Registro 2D-3D
CAT3D is a TPS developed by Mevis Informática Médica LTDA, Brasil
Recursos de segmentação e ROIs no sistema de planejamento para radioterapia MNPS-CAT3D.
Segmentação automática
Segmentação modo Paintbrush
Operações lógicas com ROIs
Importando ROIs.
CAT3D is a TPS developed by Mevis Informática Médica LTDA, Brasil
Curso MNPS 2018: Radiocirurgia. MNPS tem um módulo de planejamento de radiocirurgia estereotaxica com cone circulares.
MNPS is a Stereotactic Planning System developed by Mevis, Brazil
Curso MNPS 2018. DWI, DTI e Tractografia. Preprocessamento para o MNPSArmando Alaminos Bouza
DWI, DTI e Tractografia. Preprocessamento para o MNPS.
Como transformar DWI em DTI e tractografia e sua importação no sistema MNPS.
Uso básico do DSI-Studio. DSI-studio is developed by Fang-Cheng (Frank) Yeh.
MNPS is stereotactic Planning System developed by Mevis. Brazil.
ABDOMINAL TRAUMA in pediatrics part one.drhasanrajab
Abdominal trauma in pediatrics refers to injuries or damage to the abdominal organs in children. It can occur due to various causes such as falls, motor vehicle accidents, sports-related injuries, and physical abuse. Children are more vulnerable to abdominal trauma due to their unique anatomical and physiological characteristics. Signs and symptoms include abdominal pain, tenderness, distension, vomiting, and signs of shock. Diagnosis involves physical examination, imaging studies, and laboratory tests. Management depends on the severity and may involve conservative treatment or surgical intervention. Prevention is crucial in reducing the incidence of abdominal trauma in children.
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
Rasamanikya is a excellent preparation in the field of Rasashastra, it is used in various Kushtha Roga, Shwasa, Vicharchika, Bhagandara, Vatarakta, and Phiranga Roga. In this article Preparation& Comparative analytical profile for both Formulationon i.e Rasamanikya prepared by Kushmanda swarasa & Churnodhaka Shodita Haratala. The study aims to provide insights into the comparative efficacy and analytical aspects of these formulations for enhanced therapeutic outcomes.
Basavarajeeyam is a Sreshta Sangraha grantha (Compiled book ), written by Neelkanta kotturu Basavaraja Virachita. It contains 25 Prakaranas, First 24 Chapters related to Rogas& 25th to Rasadravyas.
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
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1. Update Course and Advanced Techniques in MNPS
(version 10.36.07, 2019-2020)
Working in “Virtual Fiducials Mode”
Armando Alaminos Bouza.
MNPS-CAT3D Development Team.
Mevis Informática Médica LTDA.
2. The “Virtual Fiducials” mode was introduced about several years
ago. So, it's nothing new. The first version of MNPS with “Virtual
Fiducials” was 10.33.03, March 2016.
Due to the importance of this concept, we will come back to it.
Before the introduction of the “Virtual Fiducials” mode we were
required to process image sequences without fiducials using
CAT3D. This solution still exists, but it is no longer the
recommended choice.
CAT3D was not created for neurosurgery, it does not have
important features such as functional neurosurgery tools, atlas
registration, and radiosurgery, and others.
3. The “Virtual Fiducials” mode aims to make the exclusive features of MNPS available to
non-stereotaxic image sequences. Some examples of resources that we can now use
without fiducials and that are not part of CAT3D are:
• Stereotactic atlas for functional neurosurgery.
• Reformat sequences and present AC-PC plane in axial, coronal and sagittal.
• Create “Probe-View” reconstructions.
• Move the cursor in the space of the patient's commissural coordinates.
• Present DBS the and position of their contacts in the patient's anatomy.
• Simulate electric fields and VTA according to DBS specific programming.
• Simulate a radiosurgery plans (SRS) with cylindrical cones.
• Tools for brain fibers (tractography) handling and rendering.
• sEEG electrodes representation.
As we will show, this feature significantly facilitates the pre-planning of radiosurgery and
functional neurosurgery, as well as the post-operative period, particularly in the
evaluation of previously implanted DBS.
4. “Virtual Fiducial” Mode
Before proceeding, it is very important to understand that in the “Virtual Fiducials” mode, the
coordinates that the MNPS presents are not registered with any stereotaxic system. The
coordinates are of a virtual stereotaxic space.
Instead of “Virtual Fiducial mode” some systems use the term “non-localized image set” or
“non-localized dataset” or “set without headframe”.
The coordinates of POIs, ROIs, and trajectories defined in the Virtual Fiducial mode only
become stereotactic after registering, merging, and importing them within a set of
stereotactic images (localized image set).
IMPORTANT:
Never use Virtual Fiducials coordinates in surgery or radiosurgery!
5. How to start a plan with Virtual Fiducials. Recommended way.
Starting from MNPS version 10.33.04, when dragging a DICOM file over the MNPShell shortcut, the dialog
that opens presents three options:
When selecting “For Virtual Fiducials Mode” the Dicom.exe system will invoke the virtual mode when
calling MNPS. In this way the MNPS enters directly into the “Virtual Fiducials” mode.
Selecting “Non-Stereotactic Image Set” will take the traditional way of processing these images with
CAT3D, which is not recommended in general.
6. How to start a plan with Virtual Fiducials. Alternative method
Sometimes the above-mentioned method is not suitable. For example, wanting to create a
new plan from images that were already imported.
In this case open MNPS. From the start menu select “Options” and then select “Virtual
Fiducials”
7. How to start a plan with Virtual Fiducials.
When selecting “Virtual Fiducial” the MNPS asks for confirmation and warns about the risks of
using coordinates of virtual fiducials in surgery. After confirming, we can run FILE and ”NEW
Plan” in virtual fiducials mode.
Never use Virtual Fiducial coordinates in surgery!
8. When in “Virtual Fiducials” (VF) mode, the execution of the “NEW Plan” is different from
the stereotaxic mode. In the case of VF, MNPS does not look for the position of real
fiducials and does not ask the operator for confirmation.
In VF mode the MNPS sets the (X=0,Y=0) of each image plane at the center of the image
pixel matrix. It then creates a set of virtual fiducials for each plane based on the ideal
design of the fiducial. The position of virtual fiducials is shown with small red crosses.
Some, or all, virtual fiducials may be hidden, it depends on whether they enter the “Field
Of View” of the image.
9. The MNPS continually reports that it is in
Virtual Fiducials mode.
Displays a WARNING in the window caption
(text at the top of the window).
Next to the regions with X, Y, Z values, the
virtual mode message appears in red.
Never use Virtual Fiducial coordinates in
surgery or radiosurgery!
10. Are we required to use axial sequences? MRI sequences are often sagittal:
12. To comfortably use non-axial sequences the MNPS has a very simple solution.
Define the position of the points AC (anterior commissure), PC (posterior commissure) and IHP (point
in the interhemispheric plane, away from the AC-PC line).
13. After defining AC, PC, IHP, we can reconstruct the axial AC-PC plane with the keyboard command
ALT-F6 or by navigating through the help menu (F1) .
We can now navigate the planes
parallel to the axial AC-PC using
<Page-Up> and <Page-Down>.
In these reformatted images we can
define POIs, for all possible purposes,
such as functional neurosurgery and
radiosurgery. We can also draw ROIs.
14. Auxiliary images on the right of the screen continue with an unusual orientation
15. But when activating maps with F6, auxiliary images revert to normal orientation
16. If the operator of MNPS does not want to work over a Coronal or Sagittal, MNPS can reformat the original
sequence into a secondary Axial sequence. Note that this tool is only available for Virtual Fiducial mode
containing Coronal or Sagittal series.
After opening the non-axial series, go to the initial menu of MNPS. Click in Options. Select “Create Axial Series”
17. The following windows will be shown.
Adjust the region that you need to be
included in the reformatted secondary
series. The desired region should be inside
the red rectangle.
18. When the desired reconstruction region is
defined press the <ENTER> key to start the
reconstruction process.
19. After MNPS creates the secondary axial series, it informs the number of slices and waits for any key to
continue.
Following that, MNPS asks permission to create a new plan with the newly created axial series, it is
recommended to accept by clicking [YES].
20. All MNPS features in stereotaxic mode can be used in “Virtual Fiducials” mode.
We just have to remember that the coordinates are not stereotaxically located.
The simulations we created in VF mode can be imported into a stereotaxic
sequence after registration and merging. Once we are satisfied with the quality
of the registration, we can import all POIs, ROIs and Brain Fibers created in the
simulation into the localized sequence.
Note that POIs with names that already exist in the stereotaxic plane are not
imported, to avoid overwriting.
22. In the case of tractography, we
are obliged to use the Virtual
Fiducials mode as the entry
point for brain fiber into the
planning.
Stereotactic sequences can only
incorporate tractography after
fusion with DWI in Virtual
Fiducials mode.
23. PET – CT in virtual fiducials mode and with registered atlas
24. In VF mode some tables that contain coordinates cannot be printed, to avoid
misuse. For example, tables with POI coordinates and radiosurgery treatment
protocols.
Remember: Never use Virtual Fiducials coordinates in surgery or radiosurgery!
25. Conclusion: The “Virtual Fiducials” mode is of great help for pre-planning stereotaxy
in general and for making post-operative assessments. We just have to remember that
the coordinates of this mode are not stereotactic.
MNPS in VF mode to pre-plan DBS implantation.