Visual Enhancement of MR Angiography Images to Facilitate Planning of Arteriovenous Malformation Interventions

Abhari, Kamyar; Baxter, Jamie; Khan, Ali R.; Peters, Terry M.; Ribaupierre, Sandrine de; Eagleson, Roy

doi:10.1145/2701425

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…The purpose of medical‐image‐data visualization is to support “the inspection, analysis and interpretation of patient data” and, more specifically, to enable “physicians to explore patient data rapidly and accurately with minimal cognitive effort” [ABK*15]. Medical image data, such as CT and MRI, are physical measurements which exhibit noise and inhomogeneities.…”

Section: Introductionmentioning

confidence: 99%

A Survey of Perceptually Motivated 3D Visualization of Medical Image Data

Preim

Baer

Cunningham

et al. 2016

Computer Graphics Forum

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International audienceThis survey provides an overview of perceptually motivated techniques for the visualization of medical image data, including physics-based lighting techniques as well as illustrative rendering that incorporate spatial depth and shape cues. Additionally, we discuss evaluations that were conducted in order to study the perceptual effects of these visualization techniques as compared to conventional techniques. These evaluations assessed depth and shape perception with depth judgment, orientation matching, and related tasks. This overview of existing techniques and their evaluation serves as a basis for defining the evaluation process of medical visualizations and to discuss a research agenda

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Section: Introductionmentioning

confidence: 99%

A Survey of Perceptually Motivated 3D Visualization of Medical Image Data

Preim

Baer

Cunningham

et al. 2016

Computer Graphics Forum

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“…Signal detection theory originated as a method of analysing experiments where auditory or visual stimuli have to be distinguished from some background noise. Since this initial use, it has been applied to the analysis of memory tasks, cognition as well as tasks within the medical domain [ABKP15].…”

Section: Signal Detection Theorymentioning

confidence: 99%

“…In [CWD*14], in contrast, for depth discrimination, tasks using simulated angiography‐like data sets stereoscopic displays proved more effective in most cases against 2D displays. Recently, [ABKP15] investigated methods to enhance MR angiography images by combining contour enhancement with stereopsis for DVR. Using a relative depth task, it was found that whilst stereopsis improved accuracy, it was most effective when combined with contour enhancement.…”

Section: Introductionmentioning

confidence: 99%

Reevaluating Reconstruction Filters for Path‐Searching Tasks in 3D

Roberts

Ivrissimtzis

2016

Computer Graphics Forum

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. AbstractIn this paper we present an experiment on stereoscopic Direct Volume Rendering (DVR), aiming at understanding the relationship between the choice of reconstruction filter and participant performance on tasks requiring spatial understanding such as 3D path-searching. The focus of our study is on the impact on task performance of the post-aliasing and smoothing produced by the reconstruction filters. We evaluated five reconstruction filters, each under two different transfer functions and two different displays with a wide range of behaviours in terms of post-aliasing and smoothing. We found that path-searching tasks commonly found in the literature, and as the one we employed here, elicit bias in the responses which should be taken into account when analysing the results. Our analysis, which employed both standard statistical tests and techniques from signal detection theory, indicates that the choice of reconstruction filter affects some aspects of the spatial understanding of the scene.

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“…Both transparency based and importance-driven volume rendering were used to highlight spatial localization and temporal progression. Abhari et al [1] emphasized the importance of contour enhancement and stereopsis in visualizing vascular structures. Their study showed that volume rendering and a non-photorealistic shading of non-contrast-enhanced MRA based models increase the perception of continuity and depth.…”

Section: Introductionmentioning

confidence: 99%

A Research Framework for Virtual-Reality Neurosurgery Based on Open-Source Tools

Fiederer

Alwanni

Volker

et al. 2019

2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)

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Fully immersive virtual reality (VR) has the potential to improve neurosurgical planning. For example, it may offer 3D visualizations of relevant anatomical structures with complex shapes, such as blood vessels and tumors. However, there is a lack of research tools specifically tailored for this area. We present a research framework for VR neurosurgery based on open-source tools and preliminary evaluation results. We showcase the potential of such a framework using clinical data of two patients and research data of one subject. As a first step toward practical evaluations, two certified senior neurosurgeons positively assessed the usefulness of the VR visualizations using head-mounted displays. The methods and findings described in our study thus provide a foundation for research and development aiming at versatile and user-friendly VR tools for improving neurosurgical planning and training.

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Visual Enhancement of MR Angiography Images to Facilitate Planning of Arteriovenous Malformation Interventions

Cited by 6 publications

References 33 publications

A Survey of Perceptually Motivated 3D Visualization of Medical Image Data

A Survey of Perceptually Motivated 3D Visualization of Medical Image Data

Reevaluating Reconstruction Filters for Path‐Searching Tasks in 3D

A Research Framework for Virtual-Reality Neurosurgery Based on Open-Source Tools

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