Introduction. Biomedical Image Analysis. Contents. Prof. Dr. Philippe Cattin. MIAC, University of Basel. Feb 22nd, of
|
|
|
- Posy Rice
- 5 years ago
- Views:
Transcription
1 Introduction Prof. Dr. Philippe Cattin MIAC, University of Basel Contents Abstract 1 Varia About Me About these Slides 2 My Research 2.1 Segmentation Segmentation of Facial Soft Tissues Segmentation of Spinal-Cord Segmentation of Spinal-Cord (2) 2.2 Organ Motion 4D MRI Mathematical Motion Model Principle/Motivation for MRgHIFU Motion Compensation Result Prediction from 2D Ultrasound MR and Ultrasound Fusion Prediction Results 2.3 Registration Smooth Deformation Model Artificial Example Example Registration with our Liver Images Example with our Liver Images Lung Motion 2.4 Augmented Reality and Navigation ARALPAN: Intra-op AR System Tablet-based Image-guided Therapy Inertia-based Navigation 2.5 Computer-Assisted Robot-guided Laser Osteotome Computer-Assisted Robot-guided Laser Osteotome SEM of Natural Bone SEM Piezoosteotome Cut Bone Laser Cut Bone Contents of :30 2 of :30
2 Abstract (2) Varia A short overview of the Medical Imaging Analysis projects that my group conducts. About Me (4) My Name: Philippe C. Cattin Apprenticeship at BBC/ABB Baden (Physics Laboratory Technician) HTL Brugg-Windisch (Computer Science) ETH Zurich (Computer Science) Ph.D. at the Institute of Robotics, ETH Zurich "Biometric Authentication System Using Human Gait" Post-Doc at the Computer Vision Lab, ETH Zurich Head of the Medical Image Analysis Group, ETH Zurich Assoc. Professor at the Medical Faculty of the University Basel Name of the group "Medical Image Analysis Center (MIAC)" 3 of :30 4 of :30
3 About these Slides Generated with hotspot/kilauea [ All hotspot presentations are generated from an XML source file A table of contents as well as all outline slides are generated automatically Also usefull for online presentations Varia (5) My Research Segmentation Allows to easily include formulas such as Hotspot/Kilauea is not usefull if you prefer a GUI Segmentation of Facial Soft Tissues Incorporation of statistical shape knowledge into the graph-cut segmentation process. (8) Masseter muscle Challenging task due to the high density artefacts 5 of :30 6 of :30
4 Segmentation Segmentation Segmentation of Spinal-Cord (9) Segmentation of Spinal-Cord (2) (10) Segmentation for sub-voxel atrophy measurement (red) background, (green) foreground, (yellow) automatic segmentation (red) background, (green) foreground, (yellow) automatic segmentation fine segmentation Precision of of the area that corresponds to in the radius 7 of :30 8 of :30
5 Organ Motion Mathematical Motion Model Organ Motion (13) 4D MRI (12) Voxelsize, Frequency 4-Dimensional statistical liver motion model Maximum Intensity Projection of the right liver lobe 4D Lung reconstruction, 24 sagittal slices, 11 stacks 9 of :30 10 of :30
6 Organ Motion Organ Motion Principle/Motivation for MRgHIFU (14) Motion Compensation Result (15) Advantages No radiation or chemotherapy No bleeding No surgery Faster recovery Minimal side effects HIFU Ablation Respiratory Motion Prediction error with the atlas based approach Principle of HIFU 11 of :30 12 of :30
7 Organ Motion Organ Motion Prediction from 2D Ultrasound (16) MR and Ultrasound Fusion (17) Given A static 3D exhalation CT image 2D/3D Ultrasound image of the liver Output Prediction of the liver/lung position 13 of :30 14 of :30
8 Prediction Results Organ Motion (18) Registration Smooth Deformation Model (20) 15 of :30 16 of :30
9 Registration Registration Artificial Example (21) Example Registration with our Liver Images (22) Variational approach that simultaneously segments and registers. Reference image Floating image Motion field Reference image Floating image Motion segmentation (continuous cuts) Motion field 17 of :30 18 of :30
10 Registration Registration Example with our Liver Images (23) Lung Motion (24) Motion segmentation and motion field 19 of :30 20 of :30
11 Augmented Reality and Navigation Tablet-based Image-guided Therapy Augmented Reality and Navigation (27) ARALPAN: Intra-op AR System (26) 21 of :30 22 of :30
12 Inertia-based Navigation Augmented Reality and Navigation (28) Computer-Assisted Robot-guided Laser Osteotome Computer-Assisted Robot-guided Laser Osteotome (30) 23 of :30 24 of :30
13 Computer-Assisted Robot-guided Laser Osteotome Computer-Assisted Robot-guided Laser Osteotome SEM of Natural Bone (31) SEM Piezoosteotome Cut Bone (32) 25 of :30 26 of :30
14 Computer-Assisted Robot-guided Laser Osteotome Laser Cut Bone (33) 27 of :30
Medical Image Analysis
Medical Image Analysis Contents Contents Ringvorlesung Computational Sciences Prof. Dr. Philippe Cattin Center for medical Image Analysis and Navigation (CIAN), University of Basel 1 Background About Me
A Non-Linear Image Registration Scheme for Real-Time Liver Ultrasound Tracking using Normalized Gradient Fields
A Non-Linear Image Registration Scheme for Real-Time Liver Ultrasound Tracking using Normalized Gradient Fields Lars König, Till Kipshagen and Jan Rühaak Fraunhofer MEVIS Project Group Image Registration,
Medicale Image Analysis
Medicale Image Analysis Registration Validation Prof. Dr. Philippe Cattin MIAC, University of Basel Prof. Dr. Philippe Cattin: Registration Validation Contents 1 Validation 1.1 Validation of Registration
Robust Tumour Tracking From 2D Imaging Using a Population-Based Statistical Motion Model
Robust Tumour Tracking From 2D Imaging Using a Population-Based Statistical Motion Model Frank Preiswerk, Patrik Arnold, Beat Fasel and Philippe C. Cattin Medical Image Analysis Center University of Basel,
Methodological progress in image registration for ventilation estimation, segmentation propagation and multi-modal fusion
Methodological progress in image registration for ventilation estimation, segmentation propagation and multi-modal fusion Mattias P. Heinrich Julia A. Schnabel, Mark Jenkinson, Sir Michael Brady 2 Clinical
Automated segmentation methods for liver analysis in oncology applications
University of Szeged Department of Image Processing and Computer Graphics Automated segmentation methods for liver analysis in oncology applications Ph. D. Thesis László Ruskó Thesis Advisor Dr. Antal
Non-rigid Registration of Preprocedural MRI and Intra-procedural CT for CT-guided Cryoablation Therapy of Liver Cancer
NA-MIC Non-rigid Registration of Preprocedural MRI and Intra-procedural CT for CT-guided Cryoablation Therapy of Liver Cancer Atsushi Yamada, Dominik S. Meier and Nobuhiko Hata Brigham and Women s Hospital
Data Fusion Virtual Surgery Medical Virtual Reality Team. Endo-Robot. Database Functional. Database
2017 29 6 16 GITI 3D From 3D to 4D imaging Data Fusion Virtual Surgery Medical Virtual Reality Team Morphological Database Functional Database Endo-Robot High Dimensional Database Team Tele-surgery Robotic
Motion artifact detection in four-dimensional computed tomography images
Motion artifact detection in four-dimensional computed tomography images G Bouilhol 1,, M Ayadi, R Pinho, S Rit 1, and D Sarrut 1, 1 University of Lyon, CREATIS; CNRS UMR 5; Inserm U144; INSA-Lyon; University
Image Segmentation and Registration
Image Segmentation and Registration Dr. Christine Tanner (tanner@vision.ee.ethz.ch) Computer Vision Laboratory, ETH Zürich Dr. Verena Kaynig, Machine Learning Laboratory, ETH Zürich Outline Segmentation
Medical Image Analysis
Computer assisted Image Analysis VT04 29 april 2004 Medical Image Analysis Lecture 10 (part 1) Xavier Tizon Medical Image Processing Medical imaging modalities XRay,, CT Ultrasound MRI PET, SPECT Generic
Combination of Markerless Surrogates for Motion Estimation in Radiation Therapy
Combination of Markerless Surrogates for Motion Estimation in Radiation Therapy CARS 2016 T. Geimer, M. Unberath, O. Taubmann, C. Bert, A. Maier June 24, 2016 Pattern Recognition Lab (CS 5) FAU Erlangen-Nu
Ch. 4 Physical Principles of CT
Ch. 4 Physical Principles of CT CLRS 408: Intro to CT Department of Radiation Sciences Review: Why CT? Solution for radiography/tomography limitations Superimposition of structures Distinguishing between
Computational Medical Imaging Analysis Chapter 4: Image Visualization
Computational Medical Imaging Analysis Chapter 4: Image Visualization Jun Zhang Laboratory for Computational Medical Imaging & Data Analysis Department of Computer Science University of Kentucky Lexington,
SIGMI. ISL & CGV Joint Research Proposal ~Image Fusion~
SIGMI ISL & CGV Joint Research Proposal ~Image Fusion~ Introduction Research Diagram What CGV Lab is interested in What ISL is interested in Research Plan Research Diagram Medical Imaging and Application
8/3/2017. Contour Assessment for Quality Assurance and Data Mining. Objective. Outline. Tom Purdie, PhD, MCCPM
Contour Assessment for Quality Assurance and Data Mining Tom Purdie, PhD, MCCPM Objective Understand the state-of-the-art in contour assessment for quality assurance including data mining-based techniques
Technical aspects of SPECT and SPECT-CT. John Buscombe
Technical aspects of SPECT and SPECT-CT John Buscombe What does the clinician need to know? For SPECT What factors affect SPECT How those factors should be sought Looking for artefacts For SPECT-CT Issues
Digital Image Processing
Digital Image Processing SPECIAL TOPICS CT IMAGES Hamid R. Rabiee Fall 2015 What is an image? 2 Are images only about visual concepts? We ve already seen that there are other kinds of image. In this lecture
A Generation Methodology for Numerical Phantoms with Statistically Relevant Variability of Geometric and Physical Properties
A Generation Methodology for Numerical Phantoms with Statistically Relevant Variability of Geometric and Physical Properties Steven Dolly 1, Eric Ehler 1, Yang Lou 2, Mark Anastasio 2, Hua Li 2 (1) University
Tomographic Reconstruction
Tomographic Reconstruction 3D Image Processing Torsten Möller Reading Gonzales + Woods, Chapter 5.11 2 Overview Physics History Reconstruction basic idea Radon transform Fourier-Slice theorem (Parallel-beam)
Deformable Segmentation using Sparse Shape Representation. Shaoting Zhang
Deformable Segmentation using Sparse Shape Representation Shaoting Zhang Introduction Outline Our methods Segmentation framework Sparse shape representation Applications 2D lung localization in X-ray 3D
Shape-Based Kidney Detection and Segmentation in Three-Dimensional Abdominal Ultrasound Images
University of Toronto Shape-Based Kidney Detection and Segmentation in Three-Dimensional Abdominal Ultrasound Images Authors: M. Marsousi, K. N. Plataniotis, S. Stergiopoulos Presenter: M. Marsousi, M.
Modeling of MR-guided HIFU for Breast and Brain Therapy
Modeling of MR-guided HIFU for Breast and Brain Therapy Douglas A. Christensen, Allison Payne, Nick Todd, Scott Almquist, Alexis Farrer and Dennis L. Parker University of Utah Salt Lake City, Utah Overview
Basic principles of MR image analysis. Basic principles of MR image analysis. Basic principles of MR image analysis
Basic principles of MR image analysis Basic principles of MR image analysis Julien Milles Leiden University Medical Center Terminology of fmri Brain extraction Registration Linear registration Non-linear
A Bayesian Framework for Estimating Respiratory Liver Motion from Sparse Measurements
A Bayesian Framework for Estimating Respiratory Liver Motion from parse Measurements Frank Preiswerk, Patrik Arnold, Beat Fasel, and Philippe C. Cattin Medical mage Analysis Center, University of Basel,
Volumetry of hypothalamic substructures by multimodal morphological image registration
Volumetry of hypothalamic substructures by multimodal morphological image registration Dominik Löchel 14.09.2011 Institute for Applied and Numerical Mathematics KIT University of the State of Baden-Württemberg
Semi-automatic Segmentation of Vertebral Bodies in Volumetric MR Images Using a Statistical Shape+Pose Model
Semi-automatic Segmentation of Vertebral Bodies in Volumetric MR Images Using a Statistical Shape+Pose Model A. Suzani, A. Rasoulian S. Fels, R. N. Rohling P. Abolmaesumi Robotics and Control Laboratory,
6th International DAAAM Baltic Conference INDUSTRIAL ENGINEERING April 2008, Tallinn, Estonia. Radu, C. & Roşca, I.C.
6th International DAAAM Baltic Conference INDUSTRIAL ENGINEERING 24-26 April 2008, Tallinn, Estonia ON THE DESIGN OF A MEDICAL IMPLANT USED FOR OSTEOSYNTHESIS OF THE TRANSSINDESMOTIC FIBULAR FRACTURE PART
Medical Images Analysis and Processing
Medical Images Analysis and Processing - 25642 Emad Course Introduction Course Information: Type: Graduated Credits: 3 Prerequisites: Digital Image Processing Course Introduction Reference(s): Insight
Learn Image Segmentation Basics with Hands-on Introduction to ITK-SNAP. RSNA 2016 Courses RCB22 and RCB54
Learn Image Segmentation Basics with Hands-on Introduction to ITK-SNAP RSNA 2016 Courses RCB22 and RCB54 RCB22 Mon, Nov 28 10:30-12:00 PM, Room S401CD RCB54 Thu, Dec 1 2:30-4:30 PM, Room S401CD Presenters:
MEDICAL IMAGE COMPUTING (CAP 5937) LECTURE 10: Medical Image Segmentation as an Energy Minimization Problem
SPRING 07 MEDICAL IMAGE COMPUTING (CAP 97) LECTURE 0: Medical Image Segmentation as an Energy Minimization Problem Dr. Ulas Bagci HEC, Center for Research in Computer Vision (CRCV), University of Central
Contours & Implicit Modelling 4
Brief Recap Contouring & Implicit Modelling Contouring Implicit Functions Visualisation Lecture 8 lecture 6 Marching Cubes lecture 3 visualisation of a Quadric toby.breckon@ed.ac.uk Computer Vision Lab.
Clinical Prospects and Technological Challenges for Multimodality Imaging Applications in Radiotherapy Treatment Planning
Clinical Prospects and Technological Challenges for Multimodality Imaging Applications in Radiotherapy Treatment Planning Issam El Naqa, PhD Assistant Professor Department of Radiation Oncology Washington
Auto-Segmentation Using Deformable Image Registration. Disclosure. Objectives 8/4/2011
Auto-Segmentation Using Deformable Image Registration Lei Dong, Ph.D. Dept. of Radiation Physics University of Texas MD Anderson Cancer Center, Houston, Texas AAPM Therapy Educational Course Aug. 4th 2011
UvA-DARE (Digital Academic Repository) Motion compensation for 4D PET/CT Kruis, M.F. Link to publication
UvA-DARE (Digital Academic Repository) Motion compensation for 4D PET/CT Kruis, M.F. Link to publication Citation for published version (APA): Kruis, M. F. (2014). Motion compensation for 4D PET/CT General
Implementation of Advanced Image Guided Radiation Therapy
Image Acquisition Course Outline Principles, characteristics& applications of the available modalities Image Processing in the T x room Image guided treatment delivery What can / can t we do in the room
MEDICAL IMAGE COMPUTING (CAP 5937) LECTURE 10: Medical Image Segmentation as an Energy Minimization Problem
SPRING 06 MEDICAL IMAGE COMPUTING (CAP 97) LECTURE 0: Medical Image Segmentation as an Energy Minimization Problem Dr. Ulas Bagci HEC, Center for Research in Computer Vision (CRCV), University of Central
Virtual Cutting in Medical Data. Institute for Real-time Computer Systems and Robotics. University of Karlsruhe, Department for Computer Science
Virtual Cutting in Medical Data A. Mazura and S. Seifert Institute for Real-time Computer Systems and Robotics Prof. Dr. U. Rembold, Prof. Dr. R. Dillmann University of Karlsruhe, Department for Computer
Arbitrary cut planes Slab control with slab thickness Projection plane adjustment Box cropping Mandible detection MPR cross-section linked views
Provides unparalleled quality and performance no need to sacrifice one for the other Enables high fidelity viewing with interactive deep supersampling Requires no GPUs or hardware accelerators a true,
Volumetric Deformable Models for Simulation of Laparoscopic Surgery
Volumetric Deformable Models for Simulation of Laparoscopic Surgery S. Cotin y, H. Delingette y, J.M. Clément z V. Tassetti z, J. Marescaux z, N. Ayache y y INRIA, Epidaure Project 2004, route des Lucioles,
A Multiple-Layer Flexible Mesh Template Matching Method for Nonrigid Registration between a Pelvis Model and CT Images
A Multiple-Layer Flexible Mesh Template Matching Method for Nonrigid Registration between a Pelvis Model and CT Images Jianhua Yao 1, Russell Taylor 2 1. Diagnostic Radiology Department, Clinical Center,
3D Slicer Overview. Andras Lasso, PhD PerkLab, Queen s University
3D Slicer Overview Andras Lasso, PhD PerkLab, Queen s University Right tool for the job Technological prototype Research tool Clinical tool Can it be done? Jalopnik.com Innovative, not robust, usually
Nonrigid Registration using Free-Form Deformations
Nonrigid Registration using Free-Form Deformations Hongchang Peng April 20th Paper Presented: Rueckert et al., TMI 1999: Nonrigid registration using freeform deformations: Application to breast MR images
Utilizing Salient Region Features for 3D Multi-Modality Medical Image Registration
Utilizing Salient Region Features for 3D Multi-Modality Medical Image Registration Dieter Hahn 1, Gabriele Wolz 2, Yiyong Sun 3, Frank Sauer 3, Joachim Hornegger 1, Torsten Kuwert 2 and Chenyang Xu 3 1
Spiral CT. Protocol Optimization & Quality Assurance. Ge Wang, Ph.D. Department of Radiology University of Iowa Iowa City, Iowa 52242, USA
Spiral CT Protocol Optimization & Quality Assurance Ge Wang, Ph.D. Department of Radiology University of Iowa Iowa City, Iowa 52242, USA Spiral CT Protocol Optimization & Quality Assurance Protocol optimization
Good Morning! Thank you for joining us
Good Morning! Thank you for joining us Deformable Registration, Contour Propagation and Dose Mapping: 101 and 201 Marc Kessler, PhD, FAAPM The University of Michigan Conflict of Interest I receive direct
Volume Illumination and Segmentation
Volume Illumination and Segmentation Computer Animation and Visualisation Lecture 13 Institute for Perception, Action & Behaviour School of Informatics Overview Volume illumination Segmentation Volume
Prostate Detection Using Principal Component Analysis
Prostate Detection Using Principal Component Analysis Aamir Virani (avirani@stanford.edu) CS 229 Machine Learning Stanford University 16 December 2005 Introduction During the past two decades, computed
Image Acquisition Systems
Image Acquisition Systems Goals and Terminology Conventional Radiography Axial Tomography Computer Axial Tomography (CAT) Magnetic Resonance Imaging (MRI) PET, SPECT Ultrasound Microscopy Imaging ITCS
Shadow casting. What is the problem? Cone Beam Computed Tomography THE OBJECTIVES OF DIAGNOSTIC IMAGING IDEAL DIAGNOSTIC IMAGING STUDY LIMITATIONS
Cone Beam Computed Tomography THE OBJECTIVES OF DIAGNOSTIC IMAGING Reveal pathology Reveal the anatomic truth Steven R. Singer, DDS srs2@columbia.edu IDEAL DIAGNOSTIC IMAGING STUDY Provides desired diagnostic
RADIOMICS: potential role in the clinics and challenges
27 giugno 2018 Dipartimento di Fisica Università degli Studi di Milano RADIOMICS: potential role in the clinics and challenges Dr. Francesca Botta Medical Physicist Istituto Europeo di Oncologia (Milano)
TG 132: Use of Image Registration and Fusion in RT
TG 132: Use of Image Registration and Fusion in RT Kristy K Brock, PhD, DABR, FAAPM Associate Professor Department of Radiation Oncology, University of Michigan Chair, AAPM TG 132: Image Registration and
Image Guidance and Beam Level Imaging in Digital Linacs
Image Guidance and Beam Level Imaging in Digital Linacs Ruijiang Li, Ph.D. Department of Radiation Oncology Stanford University School of Medicine 2014 AAPM Therapy Educational Course Disclosure Research
Multimodal Elastic Image Matching
Research results based on my diploma thesis supervised by Prof. Witsch 2 and in cooperation with Prof. Mai 3. 1 February 22 nd 2011 1 Karlsruhe Institute of Technology (KIT) 2 Applied Mathematics Department,
INDUSTRIAL SYSTEM DEVELOPMENT FOR VOLUMETRIC INTEGRITY
INDUSTRIAL SYSTEM DEVELOPMENT FOR VOLUMETRIC INTEGRITY VERIFICATION AND ANALYSIS M. L. Hsiao and J. W. Eberhard CR&D General Electric Company Schenectady, NY 12301 J. B. Ross Aircraft Engine - QTC General
Overview of Proposed TG-132 Recommendations
Overview of Proposed TG-132 Recommendations Kristy K Brock, Ph.D., DABR Associate Professor Department of Radiation Oncology, University of Michigan Chair, AAPM TG 132: Image Registration and Fusion Conflict
Comp 145 UNC-Chapel Hill. Contract II MIDAS. Submitted to. Dr. Stephen Aylward and Prof. Greg Welch. February 13, Dr. Stephen Aylward, Client
Comp 145 UNC-Chapel Hill Contract II MIDAS Submitted to Dr. Stephen Aylward and Prof. Greg Welch February 13, 2001 Dr. Stephen Aylward, Client Mike Beranek Anthony Chow Sharon Gravely Andy Mackelfresh
Deviceless respiratory motion correction in PET imaging exploring the potential of novel data driven strategies
g Deviceless respiratory motion correction in PET imaging exploring the potential of novel data driven strategies Presented by Adam Kesner, Ph.D., DABR Assistant Professor, Division of Radiological Sciences,
Segmentation and Modeling of the Spinal Cord for Reality-based Surgical Simulator
Segmentation and Modeling of the Spinal Cord for Reality-based Surgical Simulator Li X.C.,, Chui C. K.,, and Ong S. H.,* Dept. of Electrical and Computer Engineering Dept. of Mechanical Engineering, National
FOREWORD TO THE SPECIAL ISSUE ON MOTION DETECTION AND COMPENSATION
Philips J. Res. 51 (1998) 197-201 FOREWORD TO THE SPECIAL ISSUE ON MOTION DETECTION AND COMPENSATION This special issue of Philips Journalof Research includes a number of papers presented at a Philips
A Registration-Based Atlas Propagation Framework for Automatic Whole Heart Segmentation
A Registration-Based Atlas Propagation Framework for Automatic Whole Heart Segmentation Xiahai Zhuang (PhD) Centre for Medical Image Computing University College London Fields-MITACS Conference on Mathematics
A Bilinear Model for Temporally Coherent Respiratory Motion
A Bilinear Model for Temporally Coherent Respiratory Motion Frank Preiswerk (B) and Philippe C. Cattin Medical Image Analysis Center, University of Basel, Basel, Switzerland {frank.preiswerk,philippe.cattin}@unibas.ch
Finite Element Simulation of Moving Targets in Radio Therapy
Finite Element Simulation of Moving Targets in Radio Therapy Pan Li, Gregor Remmert, Jürgen Biederer, Rolf Bendl Medical Physics, German Cancer Research Center, 69120 Heidelberg Email: pan.li@dkfz.de Abstract.
Navigation System for ACL Reconstruction Using Registration between Multi-Viewpoint X-ray Images and CT Images
Navigation System for ACL Reconstruction Using Registration between Multi-Viewpoint X-ray Images and CT Images Mamoru Kuga a*, Kazunori Yasuda b, Nobuhiko Hata a, Takeyoshi Dohi a a Graduate School of
Automatic Thoracic CT Image Segmentation using Deep Convolutional Neural Networks. Xiao Han, Ph.D.
Automatic Thoracic CT Image Segmentation using Deep Convolutional Neural Networks Xiao Han, Ph.D. Outline Background Brief Introduction to DCNN Method Results 2 Focus where it matters Structure Segmentation
Segmentation Using a Region Growing Thresholding
Segmentation Using a Region Growing Thresholding Matei MANCAS 1, Bernard GOSSELIN 1, Benoît MACQ 2 1 Faculté Polytechnique de Mons, Circuit Theory and Signal Processing Laboratory Bâtiment MULTITEL/TCTS
TEMPLATE-BASED AUTOMATIC SEGMENTATION OF MASSETER USING PRIOR KNOWLEDGE
TEMPLATE-BASED AUTOMATIC SEGMENTATION OF MASSETER USING PRIOR KNOWLEDGE H.P. Ng 1,, S.H. Ong 3, P.S. Goh 4, K.W.C. Foong 1, 5, W.L. Nowinski 1 NUS Graduate School for Integrative Sciences and Engineering,
Respiratory Motion Compensation for Simultaneous PET/MR Based on Strongly Undersampled Radial MR Data
Respiratory Motion Compensation for Simultaneous PET/MR Based on Strongly Undersampled Radial MR Data Christopher M Rank 1, Thorsten Heußer 1, Andreas Wetscherek 1, and Marc Kachelrieß 1 1 German Cancer
Digital Image Processing Lectures 1 & 2
Lectures 1 & 2, Professor Department of Electrical and Computer Engineering Colorado State University Spring 2013 Introduction to DIP The primary interest in transmitting and handling images in digital
Intraoperative Prostate Tracking with Slice-to-Volume Registration in MR
Intraoperative Prostate Tracking with Slice-to-Volume Registration in MR Sean Gill a, Purang Abolmaesumi a,b, Siddharth Vikal a, Parvin Mousavi a and Gabor Fichtinger a,b,* (a) School of Computing, Queen
iplan RT Image Advanced Contouring Workstation - Driving Physician Collaboration
iplan RT Image Advanced Contouring Workstation - Driving Physician Collaboration The iplan Contouring Workstation offers unique and innovative capabilities for faster contouring and consistent segmentation
X-ray Based Craniofacial Visualization and Surgery Simulation
X-ray Based Craniofacial Visualization and Surgery Simulation Junjun Pan 1, Jian J Zhang 1, Yanning Zhang 2, Hong Zhou 3 E-mail: pjunjun@bournemouth.ac.uk, jzhang@bournemouth.ac.uk ynzhang@nwpu.edu.cn,
Automatic segmentation of the cortical grey and white matter in MRI using a Region Growing approach based on anatomical knowledge
Automatic segmentation of the cortical grey and white matter in MRI using a Region Growing approach based on anatomical knowledge Christian Wasserthal 1, Karin Engel 1, Karsten Rink 1 und André Brechmann
Computed tomography (Item No.: P )
Computed tomography (Item No.: P2550100) Curricular Relevance Area of Expertise: Biology Education Level: University Topic: Modern Imaging Methods Subtopic: X-ray Imaging Experiment: Computed tomography
Medical Image Analysis Active Shape Models
Medical Image Analysis Active Shape Models Mauricio Reyes, Ph.D. mauricio.reyes@istb.unibe.ch ISTB - Institute for Surgical Technology and Biomechanics University of Bern Lecture Overview! Statistical
Quantitative Analysis and Visualization with 3D Slicer
Surgical Planning Laboratory Brigham and Women s Hospital Boston, Massachusetts USA a teaching affiliate of Harvard Medical School Quantitative Analysis and Visualization with 3D Slicer Jeffrey Yapp, PhD
Volume visualization. Volume visualization. Volume visualization methods. Sources of volume visualization. Sources of volume visualization
Volume visualization Volume visualization Volumes are special cases of scalar data: regular 3D grids of scalars, typically interpreted as density values. Each data value is assumed to describe a cubic
Fast CT-CT Fluoroscopy Registration with Respiratory Motion Compensation for Image-Guided Lung Intervention
Fast CT-CT Fluoroscopy Registration with Respiratory Motion Compensation for Image-Guided Lung Intervention Po Su a,b, Zhong Xue b*, Kongkuo Lu c, Jianhua Yang a, Stephen T. Wong b a School of Automation,
Towards deformable registration for augmented reality in robotic assisted partial nephrectomy
Towards deformable registration for augmented reality in robotic assisted partial nephrectomy Supervisor: Elena De Momi, PhD Co-supervisor: Dott. Ing. Sara Moccia Author: Anna Morelli, 853814 Academic
Contours & Implicit Modelling 1
Contouring & Implicit Modelling Visualisation Lecture 8 Institute for Perception, Action & Behaviour School of Informatics Contours & Implicit Modelling 1 Brief Recap Contouring Implicit Functions lecture
arxiv: v1 [cs.cv] 6 Jun 2017
![arxiv: v1 [cs.cv] 6 Jun 2017](/thumbs/96/128307097.jpg "arxiv: v1 [cs.cv] 6 Jun 2017")
Volume Calculation of CT lung Lesions based on Halton Low-discrepancy Sequences Liansheng Wang a, Shusheng Li a, and Shuo Li b a Department of Computer Science, Xiamen University, Xiamen, China b Dept.
ADAPTIVE GRAPH CUTS WITH TISSUE PRIORS FOR BRAIN MRI SEGMENTATION
ADAPTIVE GRAPH CUTS WITH TISSUE PRIORS FOR BRAIN MRI SEGMENTATION Abstract: MIP Project Report Spring 2013 Gaurav Mittal 201232644 This is a detailed report about the course project, which was to implement
CT IMAGE PROCESSING IN HIP ARTHROPLASTY
U.P.B. Sci. Bull., Series C, Vol. 75, Iss. 3, 2013 ISSN 2286 3540 CT IMAGE PROCESSING IN HIP ARTHROPLASTY Anca MORAR 1, Florica MOLDOVEANU 2, Alin MOLDOVEANU 3, Victor ASAVEI 4, Alexandru EGNER 5 The use
Snakes, level sets and graphcuts. (Deformable models)
INSTITUTE OF INFORMATION AND COMMUNICATION TECHNOLOGIES BULGARIAN ACADEMY OF SCIENCE Snakes, level sets and graphcuts (Deformable models) Centro de Visión por Computador, Departament de Matemàtica Aplicada
Fully Automatic Endoscope Calibration for Intraoperative Use
Fully Automatic Endoscope Calibration for Intraoperative Use Christian Wengert, Mireille Reeff, Philippe C. Cattin, Gábor Székely Computer Vision Laboratory, ETH Zurich, 8092 Zurich, Switzerland {wengert,
osteoma with human clinical data
Bone thermal modelling for magnetic resonance guided high intensity focused ultrasound therapy of osteoid osteoma with human clinical data by Alexander Chisholm A thesis submitted in conformity with the
The team. Disclosures. Ultrasound Guidance During Radiation Delivery: Confronting the Treatment Interference Challenge.
Ultrasound Guidance During Radiation Delivery: Confronting the Treatment Interference Challenge Dimitre Hristov Radiation Oncology Stanford University The team Renhui Gong 1 Magdalena Bazalova-Carter 1
Nonrigid Surface Modelling. and Fast Recovery. Department of Computer Science and Engineering. Committee: Prof. Leo J. Jia and Prof. K. H.
Nonrigid Surface Modelling and Fast Recovery Zhu Jianke Supervisor: Prof. Michael R. Lyu Committee: Prof. Leo J. Jia and Prof. K. H. Wong Department of Computer Science and Engineering May 11, 2007 1 2
Biomedical Image Processing for Human Elbow
Biomedical Image Processing for Human Elbow Akshay Vishnoi, Sharad Mehta, Arpan Gupta Department of Mechanical Engineering Graphic Era University Dehradun, India akshaygeu001@gmail.com, sharadm158@gmail.com
Machine Learning for Medical Image Analysis. A. Criminisi
Machine Learning for Medical Image Analysis A. Criminisi Overview Introduction to machine learning Decision forests Applications in medical image analysis Anatomy localization in CT Scans Spine Detection
CSE 145/237D FINAL REPORT. 3D Reconstruction with Dynamic Fusion. Junyu Wang, Zeyangyi Wang
CSE 145/237D FINAL REPORT 3D Reconstruction with Dynamic Fusion Junyu Wang, Zeyangyi Wang Contents Abstract... 2 Background... 2 Implementation... 4 Development setup... 4 Real time capturing... 5 Build
EUSIPCO
EUSIPCO 2013 1569743181 SEGMENTATION OF RIB BONES FROM MR DATA USING TRACKING APPROACH AND POLYNOMIAL PARAMETRIZATION Harri Pölönen 1, Gerald Schubert 2 1 VTT Technical Research Centre of Finland Tampere,
Extraction and recognition of the thoracic organs based on 3D CT images and its application
1 Extraction and recognition of the thoracic organs based on 3D CT images and its application Xiangrong Zhou, PhD a, Takeshi Hara, PhD b, Hiroshi Fujita, PhD b, Yoshihiro Ida, RT c, Kazuhiro Katada, MD
NON OB ULTRASOUND MORPHOMETRICS AS BIOMARKERS
NON OB ULTRASOUND MORPHOMETRICS AS BIOMARKERS Brian S Garra Washington DC VA Medical Center and Division of Imaging & Applied Mathematics, OSEL, CDRH, FDA GOALS Review Major Types of Clinical Ultrasonic
Chapter 3 Set Redundancy in Magnetic Resonance Brain Images
16 Chapter 3 Set Redundancy in Magnetic Resonance Brain Images 3.1 MRI (magnetic resonance imaging) MRI is a technique of measuring physical structure within the human anatomy. Our proposed research focuses
A Navigation System for Minimally Invasive Abdominal Intervention Surgery Robot
A Navigation System for Minimally Invasive Abdominal Intervention Surgery Robot Weiming ZHAI, Yannan ZHAO and Peifa JIA State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory
AN essential part of any computer-aided surgery is planning
1 A Model Based Validation Scheme for Organ Segmentation in CT Scan Volumes Hossein Badakhshannoory, Student Member, IEEE, and Parvaneh Saeedi, Member, IEEE Abstract In this work, we propose a novel approach
COMPUTER GRAPHICS. Computer Multimedia Systems Department Prepared By Dr Jamal Zraqou
COMPUTER GRAPHICS Computer Multimedia Systems Department Prepared By Dr Jamal Zraqou Introduction What is Computer Graphics? Applications Graphics packages What is Computer Graphics? Creation, Manipulation
Computed tomography of simple objects. Related topics. Principle. Equipment TEP Beam hardening, artefacts, and algorithms
Related topics Beam hardening, artefacts, and algorithms Principle The CT principle is demonstrated with the aid of simple objects. In the case of very simple targets, only a few images need to be taken
A fluence convolution method to account for respiratory motion in three-dimensional dose calculations of the liver: A Monte Carlo study
A fluence convolution method to account for respiratory motion in three-dimensional dose calculations of the liver: A Monte Carlo study Indrin J. Chetty, a) Mihaela Rosu, Neelam Tyagi, Lon H. Marsh, Daniel