Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms

Ip, Cheuk Yiu; Varshney, Amitabh; JáJá, Joseph F.

doi:10.1109/tvcg.2012.231

Cited by 54 publications

(9 citation statements)

References 39 publications

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“…Furthermore, all responses should fully address all the relevant parts of that are aimed to be mapped, that is, the responses should be exhaustive. Originally developed for the corporate world [ 12 – 14 ], the principle of mutually exclusive and collectively exhaustive questioning has been used in several medical research studies due to its ability to distinguish between differing items while ensuring that all items are enlightened [ 15 – 18 ].…”

Section: Methodsmentioning

confidence: 99%

Danish first aid books compliance with the new evidence-based non-resuscitative first aid guidelines

Jensen

Møller

Viereck

et al. 2018

Scand J Trauma Resusc Emerg Med

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BackgroundThe European Resuscitation Council (ERC) released new guidelines on resuscitation in 2015. For the first time, the guidelines included a separate chapter on first aid for laypersons. We analysed the current major Danish national first aid books to identify potential inconsistencies between the current books and the new evidence-based first aid guidelines.MethodsWe identified first aid books from all the first aid courses offered by major Danish suppliers. Based on the new ERC first aid guidelines, we developed a checklist of 26 items within 16 different categories to assess the content; this checklist was adapted following the principle of mutually exclusive and collectively exhaustive questioning. To assess the agreement between four raters, Fleiss’ kappa test was used. Items that did not reach an acceptable kappa score were excluded.ResultsWe evaluated 10 first aid books used for first aid courses and published between 2009 and 2015. The content of the books complied with the new in 38% of the answers.In 12 of the 26 items, there was less than 50% consistency. These items include proximal pressure points and elevation of extremities for the control of bleeding, use of cervical collars, treatment for an open chest wound, burn dressing, dental avulsion, passive leg raising, administration of bronchodilators, adrenaline, and aspirin.ConclusionsDanish course material showed significant inconsistencies with the new evidence-based first aid guidelines. The new knowledge from the evidence-based guidelines should be incorporated into revised and updated first aid course material.Electronic supplementary materialThe online version of this article (10.1186/s13049-018-0472-7) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Danish first aid books compliance with the new evidence-based non-resuscitative first aid guidelines

Jensen

Møller

Viereck

et al. 2018

Scand J Trauma Resusc Emerg Med

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show abstract

“…The shape of the widget might not capture the ideal shape given the data or the user might lack the prior knowledge that is required for this task. Alternatively, hierarchical exploration of normalized graph cut decision trees [ 39 ] can be used. This graph cut method results in a set of components (i.e.…”

Section: Theory I: Transfer Functions and 2d Histogramsmentioning

confidence: 99%

“…Here, we show that non-brain voxels misclassified as GM can largely be corrected using a multi-dimensional transfer function that is specified based on a two-dimensional (2D) histogram representation [ 36 – 39 ] of three-dimensional (3D) MRI brain data. We demonstrate that this transfer function offers an efficient way to single out non-brain tissue voxels.…”

Section: Introductionmentioning

confidence: 99%

“…Likewise, there are alternative ways of defining clusters in an image to the normalized graph cut algorithm that we have used here [ 43 – 46 ]. While all these methods have their merit, we decided to use normalized-cut multilevel segmentation since it already has been shown to work successfully on the 2D histogram representations of volumetric data [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

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A scalable method to improve gray matter segmentation at ultra high field MRI

et al. 2018

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High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.

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“…In an extension of this idea, local histograms are used to expose smaller peaks that are not easily detected in the global histogram [75,76]. Semi-automatic methods that rely on segmentation or feature space analysis to identify unique tissues are also utilized [39,80]. Another extension builds on presets provided by recurring settings as motifs [109].…”

Section: High-level Semantics and Work Flowmentioning

confidence: 99%

Medical Volume Visualization Beyond Single Voxel Values

Lindholm¹

2014

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Acknowledgments AbstractMedical visualization involves many complex decisions for both the user and the imaging algorithms. This thesis aims to improve medical volume visualization through a series of technical contributions to aid such decision processes. Improvements are achieved by using more data, beyond single voxels, in the associated visual analyses.Simultaneous visualization of multiple data sources and different data formats is rapidly becoming a necessity. This is due to both the growing number of data producing image acquisition techniques as well as the increase in geometric data representations that can be created. Maintaining high rendering performance under these circumstances is challenging, but necessary, to support an exploratory visualization process. This thesis proposes two algorithms to address this challenge: a multi-volume approach that applies binary-space partitioning to solve painters' algorithm geometrically and a rendering algorithm for hybrid data that improves the management of the available graphics memory.Additional information for decision support is often derived from the captured image data. Classification techniques, in particular, often utilize secondary information sources or neighborhood analysis as means to improve specificity. One example is a proposed algorithm that improves visualization of blood vessels by automatically optimizing visualization parameters based on observed vesselness. This thesis also proposes algorithms involving neighborhood analysis, with a particular focus on domain specific classification knowledge provided by the user. One algorithm provides the ability to semantically state spatial relations between tissues based on encoded material information. Another algorithm improves the representation of discrete features by integrating the users' knowledge in the reconstruction step of the visualization pipeline.Many of the methods proposed in this thesis can also be applied to other domains, but are all described here in the context of medical volume visualization as most of the research has been performed within this field.v Populärvetenskaplig SammanfattningMedicinsk visualisering involverar en mängd komplexa beslut, både för användaren och för bildsystemet. I många fall handlar dessa beslut om vilken information som skall visas och hur den skall visas. Utfallen av dessa beslut kan potentiellt förbättras ju mer data som inkluderas i beslutsprocessen bortom enskilda voxlar. Den här avhandlingen avser att förbättra och effektivisera medicinsk volumsvisualisering genom en rad tekniska forskningsbidrag.Samtidig visualisering av multipla datakällor och olika dataformat är snabbt på väg att bli en nödvändighet. Dels på grund av det växande antalet dataproducerande bildmetoder, men även på grund av det stigande antalet geometriska representationer som kan skapas. Att producera snabba effektiva renderingar under dessa förutsättningar är svårt, men också nödvändigt för att stödja den ofta explorativa visualiseringsprocessen. Ytterligare information för besluts...

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Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms

Cited by 54 publications

References 39 publications

Danish first aid books compliance with the new evidence-based non-resuscitative first aid guidelines

Danish first aid books compliance with the new evidence-based non-resuscitative first aid guidelines

A scalable method to improve gray matter segmentation at ultra high field MRI

Medical Volume Visualization Beyond Single Voxel Values

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