The VesselGlyph: Focus & Context Visualization in CT-Angiography

Similar documents
The VesselGlyph: Focus & Context Visualization in CT-Angiography

Non-linear Model Fitting to Parameterize Diseased Blood Vessels

FINDING THE TRUE EDGE IN CTA

Blood Vessel Visualization on CT Data

Vessel Explorer: a tool for quantitative measurements in CT and MR angiography

Medical Image Processing: Image Reconstruction and 3D Renderings

Medical Visualization - Volume Rendering. J.-Prof. Dr. Kai Lawonn

THE F3D TOOLS FOR PROCESSING AND VISUALIZATION OF VOLUMETRIC DATA

Diagnostic Relevant Visualization of Vascular Structures

Volume Visualization

Vessel Visualization using Curved Surface Reformation

Volume Visualization. Part 1 (out of 3) Volume Data. Where do the data come from? 3D Data Space How are volume data organized?

TECHNICAL REPORT. Smart Linking of 2D and 3D Views in Medical Applications

Tomographic Reconstruction

[PDR03] RECOMMENDED CT-SCAN PROTOCOLS

Mirrored LH Histograms for the Visualization of Material Boundaries

Contrast Enhancement with Dual Energy CT for the Assessment of Atherosclerosis

Modeling and preoperative planning for kidney surgery

CIS 467/602-01: Data Visualization

4D Magnetic Resonance Analysis. MR 4D Flow. Visualization and Quantification of Aortic Blood Flow

IMPAX Volume Viewing 3D Visualization & Segmentation

Image Acquisition Systems

Volume Illumination and Segmentation

Fast Visualization of Object Contours by Non-Photorealistic Volume Rendering

Computer-Tomography I: Principles, History, Technology

Advanced Curved Planar Reformation: Flattening of Vascular Structures

Data Visualization (DSC 530/CIS )

Fundamentals of CT imaging

COMPREHENSIVE QUALITY CONTROL OF NMR TOMOGRAPHY USING 3D PRINTED PHANTOM

Vessel Visualization using Curvicircular Feature Aggregation

Bilateral Depth Filtering for Enhanced Vessel Reformation

Data Visualization (CIS/DSC 468)

Machine Learning for Medical Image Analysis. A. Criminisi

An Advanced Data Structure for Large Medical Datasets

Centerline Reformations of Complex Vascular Structures

icatvision Quick Reference

Multimodal Vessel Visualization of Mouse Aorta PET/CT Scans

Display. Introduction page 67 2D Images page 68. All Orientations page 69 Single Image page 70 3D Images page 71

Coronary Artery Calcium Quantification in Contrast-enhanced Computed Tomography Angiography

CT Basics Principles of Spiral CT Dose. Always Thinking Ahead.

Automatic Ascending Aorta Detection in CTA Datasets

Extraction and recognition of the thoracic organs based on 3D CT images and its application

3D Surface Reconstruction of the Brain based on Level Set Method

3/27/2012 WHY SPECT / CT? SPECT / CT Basic Principles. Advantages of SPECT. Advantages of CT. Dr John C. Dickson, Principal Physicist UCLH

Computer-Tomography II: Image reconstruction and applications

Fast Segmentation of Kidneys in CT Images

AORTA CTA VPMC-12419

Shadow casting. What is the problem? Cone Beam Computed Tomography THE OBJECTIVES OF DIAGNOSTIC IMAGING IDEAL DIAGNOSTIC IMAGING STUDY LIMITATIONS

Contours & Implicit Modelling 4

Arbitrary cut planes Slab control with slab thickness Projection plane adjustment Box cropping Mandible detection MPR cross-section linked views

Computational Medical Imaging Analysis Chapter 4: Image Visualization

Interactive Boundary Detection for Automatic Definition of 2D Opacity Transfer Function

Vessel Tracking in Peripheral CTA Datasets An Overview

CTA HEAD Perfusion AqONE without and with IV Contrast

Enhanced material contrast by dual-energy microct imaging

Image Post-Processing, Workflow, & Interpretation

Direct Volume Rendering. Overview

Overview. Direct Volume Rendering. Volume Rendering Integral. Volume Rendering Integral Approximation

A Workflow for Improving Medical Visualization of Semantically Annotated CT-Images

Smart Super Views A Knowledge-Assisted Interface for Medical Visualization

SIGMI Meeting ~Image Fusion~ Computer Graphics and Visualization Lab Image System Lab

US 1.

Data Visualization (DSC 530/CIS )

8. Tensor Field Visualization

VieW 3D. 3D Post-Processing WorKstation THE THIRD DIMENSION. Version 3.1

8/3/2017. Contour Assessment for Quality Assurance and Data Mining. Objective. Outline. Tom Purdie, PhD, MCCPM

Visually Supporting Depth Perception in Angiography Imaging

Human Heart Coronary Arteries Segmentation

Operator s manual. Operator s Manual WhiteFox Imaging V0C (15) 10/2017 NCBCEN020C

Ch. 4 Physical Principles of CT

Management and Visualization of images with labeled segments:

Previously... contour or image rendering in 2D

Volume Rendering. Computer Animation and Visualisation Lecture 9. Taku Komura. Institute for Perception, Action & Behaviour School of Informatics

Conveying 3D Shape and Depth with Textured and Transparent Surfaces Victoria Interrante

How to Adjust the 16-Bit CLUT (Color Look Up Table) Editor in OsiriX

Multi-slice CT Image Reconstruction Jiang Hsieh, Ph.D.

Automated segmentation methods for liver analysis in oncology applications

GPU-Accelerated Deep Shadow Maps

Advanced MRI Techniques (and Applications)

RADIOMICS: potential role in the clinics and challenges

Hardware Acceleration for Vessel Visualization Tasks

Automatic Transfer Function Specification for Visual Emphasis of Coronary Artery Plaque

Construction of Voxel-type Phantom Based on Computed Tomographic Data of RANDO Phantom for the Monte Carlo Simulations

High dynamic range magnetic resonance flow imaging in the abdomen

Optimisation of Toshiba Aquilion ONE Volume Imaging

Scalar Data. CMPT 467/767 Visualization Torsten Möller. Weiskopf/Machiraju/Möller

Automatic Segmentation of the Aortic Dissection Membrane from 3D CTA Images

Motion artifact detection in four-dimensional computed tomography images

Scalar Data. Visualization Torsten Möller. Weiskopf/Machiraju/Möller

Functional Analysis of the Vertebral Column Based on MR and Direct Volume Rendering

cs6630 November TRANSFER FUNCTIONS Alex Bigelow University of Utah

ThE ultimate, INTuITIVE Mr INTErFAcE

Using Pinnacle 16 Deformable Image registration in a re-treat scenario

RADIOLOGY AND DIAGNOSTIC IMAGING

Medical Image Analysis

Vessel Tracking in Peripheral CTA Datasets an overview

Phantom-based evaluation of a semi-automatic segmentation algorithm for cerebral vascular structures in 3D ultrasound angiography (3D USA)

3D Object Representation. Michael Kazhdan ( /657)

Presentation and analysis of multidimensional data sets

Fast Visualization of Object Contours by Non-Photorealistic Volume Rendering

Transcription:

The VesselGlyph: Focus & Context Visualization in CT-Angiography Matúš Straka M. Šrámek, A. La Cruz E. Gröller, D. Fleischmann

Contents Motivation:» Why again a new visualization method for vessel data? Concept of the VesselGlyph Patient data examples Algorithm Conclusion 2/28

Vessel Visualization Basics Visualization of vessels (angiography)» Diseased vessels, e.g. PAOD» Depiction of soft plaque, calcifications, occlusions, Datasets acquired using helical CT scanner Vessels enhanced in CT-Angiography images by injection of contrast agent CT-Angiography data are huge (1200+ slices) 3/28

4/28

Vessel Visualization Basics Visualization of diseased vessels (PAOD) CT-Angiography data are huge (1200+ slices) Tissue density ranges can overlap, tissues can be spatially very close» Problematic segmentation» Only centerlines of the main vessels often available Aorta (vessel) Vertebra (bone) Vessels represent a small part of the dataset The rest is important as an anatomic context 5/28

The AngioVis Project Interdisciplinary project aimed at visualization and assessment of vessels in 3D CT-Angiography datasets» Development of new methods and SW tools Cooperation of:» Austrian Academy of Sciences» Vienna University of Technology, Austria» General Hospital (AKH) of Vienna, Austria» Stanford Medical Centre, USA 6/28

Vessel Visualization Basics 7/28 Maximum Intensity Projection (MIP) Curved Planar Reformation (CPR) Direct Volume Rendering (DVR)

Why something new? Objects in focus (vessels) need to be enhanced in the images Anatomic context is important for orientation in the images» No relevant anatomic context in CPR images» Depth perception ambiguous in MIP images» Occlusion in MIP and DVR images Anatomic context should not dominate the images Different visualization techniques and/or parameters for focus and context are needed 8/28

The VesselGlyph Is a concept for:» Spatially dependent definition of focus and context areas» Combination of various visualization techniques and/or parameters therein» If necessary, allows also smooth transition in between Focus and context areas are defined by:» Vessel centerlines» Voxel-to-centerline distances and viewing vector 9/28

The VesselGlyph Concept Soft Tissue Vessel Focus Area Bone Dataset Slice View Direction Context Area 10/28

VesselGlyph Construction Dataset Slice Context Focus Context Transitional Areas 11/28

VesselGlyph Application For tubular structures, VesselGlyph» can be used as 2D-to-3D interface» Allows easy modification of parameters (size, layout, technique, ) in 2D widget» Swept along the centerline for 3D results 12/28

VesselGlyph Application Vessel 13/28

VesselGlyph Layouts Dataset Context Focus Context Transitional Areas 14/28

VesselGlyph Layouts Dataset Context Focus Context Transitional Areas 15/28

VesselGlyph Layouts Dataset Focus Context Transitional 16/28

VesselGlyph Layouts Dataset Context Focus Transitional Areas 17/28

Focus & Context Definition r r α d f f = f ( d, v) / c or r v r View Dir f f = f ( d, α) / c 18/28

Tubular VesselGlyph» Normal DVR for focus» Transparent DVR for context View Dir Motivation» Concept» Examples»Algorithm»Conclusion 19/28

20/28

Thick-Slab VesselGlyph View Dir» Normal DVR for focus» Transparent DVR for context 21/28

CPR-in-DVR VesselGlyph focus c View Dir» CPR for focus» DVR for context Motivation» Concept» Examples»Algorithm»Conclusion 22/28

Foreground-Cleft» DVR for focus» DVR for context View Dir Motivation» Concept» Examples»Algorithm»Conclusion 23/28

Foreground Cleft with Occlusion Lines View Dir» DVR for focus» DVR for context Rear view Front view Motivation» Concept» Examples»Algorithm»Conclusion 24/28

Algorithm Three-stage processing:» 1. Distance-to-centerline evaluation» 2. Focus and context partial rendering» 3. Compositing of partial renderings Compositing of partial renderings can be:» Implicit (F/C rendered at once)» Based on distance» Based on data density 25/28

Algorithm Extension of standard DVR algorithm Opacity depends also on spatial location Transparency modifier coefficient:» Influences opacity transfer function» Different for focus and context» Works for DVR+DVR layouts f f / c Special cases - DVR+CPR, DVR+MIP 26/28

Conclusion & Future Work VesselGlyph:» Is a generalization of various visualization techniques (DVR, CPR, MIP, )» Displays unoccluded objects in a correct anatomic context Clinical evaluation in progress Extension to arbitrary shapes using distance fields 27/28

Thank you for your attention matus.straka@assoc.oeaw.ac.at http://www.viskom.oeaw.ac.at/~straka/angiovis 28/28