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The stack mode review of volumetric datasets: applications for urinary stone disease
Örebro University, School of Health and Medical Sciences, Örebro University, Sweden.
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

During the last decades the acquisition and visualization of radiological images have rapidly evolved. The increasing amounts of volumetric image data particularly from modern CT systems necessitate a constant evolution of the radiological visualization techniques.

The dominating display mode for volumetric images has been the stack mode display since its introduction in computerized image review. In the increasing amounts of image data, the stack mode display needs to be analyzed so that the information content in the high resolution datasets can be transformed into clinically relevant information for the management of the individual patient. In the present thesis some aspects of the stack mode display were analyzed using for the most part the size estimation of urinary stones in unenhanced CT as a model.

The estimated size has an important correlation to the prognosis for spontaneous passage of an obstructing ureteral stone. In the present thesis the reader variations in the size estimation of urinary stones were quantified, using different visualization parameters and after an attempt to reduce the variations with a training session for the readers. The influence on the estimated stone size of CT image post processing parameters was quantified. A segmentation algorithm was developed and demonstrated to reduce the reader variability through reader independent computer aid. One limitation of the stack mode display concerns three-dimensional shapes, which was modeled by a comparison between the estimated length and width of urinary stones in two- and three-dimensional segmentation. The increasing number of image slices in the acquisitions introduces a need for efficient navigation of the image volumes. In the present thesis the navigation of CT datasets using different user interface devices was evaluated.

The rapid evolution of the MRI and CT systems necessitates a constant refinement and evaluation of the cornerstone for radiological volumetric reviewing – the stack mode display of volumetric datasets.

Place, publisher, year, edition, pages
Örebro: Örebro universitet , 2013. , p. 61
Series
Örebro Studies in Medicine, ISSN 1652-4063 ; 91
Keywords [en]
stack mode display, image visualization, image perception, computed tomography, urinary stones, urolithiasis, PACS
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Medicine
Identifiers
URN: urn:nbn:se:oru:diva-30324ISBN: 978-91-7668-948-6 (print)OAI: oai:DiVA.org:oru-30324DiVA, id: diva2:643078
Public defence
2013-10-04, Bohmanssonsalen, Universitetssjukhuset i Örebro, Örebro, 09:00 (Swedish)
Opponent
Supervisors
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2017-10-17Bibliographically approved
List of papers
1. Alternative user interface devices for improved navigation of CT datasets
Open this publication in new window or tab >>Alternative user interface devices for improved navigation of CT datasets
2011 (English)In: Journal of digital imaging, ISSN 0897-1889, E-ISSN 1618-727X, Vol. 24, no 1, p. 126-134Article in journal (Refereed) Published
Abstract [en]

The workflow in radiology departments has changed dramatically with the transition to digital PACS, especially with the shift from tile mode to stack mode display of volumetric images. With the increasing number of images in routinely captured datasets, the standard user interface devices (UIDs) become inadequate. One basic approach to improve the navigation of the stack mode datasets is to take advantage of alternative UIDs developed for other domains, such as the computer game industry. We evaluated three UIDs both in clinical practice and in a task-based experiment. After using the devices in the daily image interpretation work, the readers reported that both of the tested alternative UIDs were better in terms of ergonomics compared to the standard mouse and that both alternatives were more efficient when reviewing large CT datasets. In the task-based experiment, one of the tested devices was faster than the standard mouse, while the other alternative was not significantly faster. One of the tested alternative devices showed a larger number of traversed images during the task. The results indicate that alternative user interface devices can improve the navigation of stack mode datasets and that radiologists should consider the potential benefits of alternatives to the standard mouse.

Place, publisher, year, edition, pages
Springer, 2011
Keywords
navigation, user interface, PACS, computed tomography
National Category
Medical and Health Sciences Radiology, Nuclear Medicine and Medical Imaging
Research subject
Medicine
Identifiers
urn:nbn:se:oru:diva-12074 (URN)10.1007/s10278-009-9252-2 (DOI)000286469600014 ()19949832 (PubMedID)2-s2.0-79751523933 (Scopus ID)
Available from: 2010-10-05 Created: 2010-10-05 Last updated: 2017-12-12Bibliographically approved
2. Making renal stones change size: impact of CT image post processing and reader variability
Open this publication in new window or tab >>Making renal stones change size: impact of CT image post processing and reader variability
2011 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 21, no 10, p. 2218-2225Article in journal (Refereed) Published
Abstract [en]

Objectives The objectives of this study were to quantify the impact of image post-processing parameters on the apparent renal stone size, and to quantify the intra- and inter-reader variability in renal stone size estimation. Methods Fifty CT datasets including a renal or ureteral stone were included retrospectively during a prospective inclusion period. Each of the CT datasets was post-processed in different ways regarding slice thickness, slice increment and window setting. In the first part of the study a single reader repeated size estimations for the renal stones using different post-processing parameters. In the intra-reader variability experiment one reader reported size estimations for the same images with a one-week interval. The inter-reader variability data were obtained from 11 readers reporting size estimations for the same renal stones. Results The apparent stone size differed according to image post-processing parameters with the largest mean differences seen with regard to the window settings experiment (1.5 mm, p < 0.001) and slice thickness (0.8 mm, p < 0.001). Changes in parameters introduced a bias and a pseudo-random variability. The inter-reader variability was considerably larger than the intra-reader variability. Conclusion Our results indicate a need for the standardisation of making measurements on CT images.

National Category
Medical and Health Sciences
Research subject
Medicine
Identifiers
urn:nbn:se:oru:diva-18641 (URN)10.1007/s00330-011-2171-x (DOI)000294471100027 ()
Available from: 2011-09-30 Created: 2011-09-29 Last updated: 2017-12-08Bibliographically approved
3. Urinary stone size estimation: Can we reduce the reader variations?
Open this publication in new window or tab >>Urinary stone size estimation: Can we reduce the reader variations?
(English)Manuscript (preprint) (Other academic)
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Radiology
Identifiers
urn:nbn:se:oru:diva-30363 (URN)
Available from: 2013-08-29 Created: 2013-08-29 Last updated: 2017-10-17Bibliographically approved
4. Urinary stone size estimation: a new segmentation algorithm-based CT method
Open this publication in new window or tab >>Urinary stone size estimation: a new segmentation algorithm-based CT method
Show others...
2012 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 22, no 4, p. 731-737Article in journal (Refereed) Published
Abstract [en]

The size estimation in CT images of an obstructing ureteral calculus is important for the clinical management of a patient presenting with renal colic. The objective of the present study was to develop a reader independent urinary calculus segmentation algorithm using well-known digital image processing steps and to validate the method against size estimations by several readers. Fifty clinical CT examinations demonstrating urinary calculi were included. Each calculus was measured independently by 11 readers. The mean value of their size estimations was used as validation data for each calculus. The segmentation algorithm consisted of interpolated zoom, binary thresholding and morphological operations. Ten examinations were used for algorithm optimisation and 40 for validation. Based on the optimisation results three segmentation method candidates were identified. Between the primary segmentation algorithm using cubic spline interpolation and the mean estimation by 11 readers, the bias was 0.0 mm, the standard deviation of the difference 0.26 mm and the Bland-Altman limits of agreement 0.0 +/- 0.5 mm. The validation showed good agreement between the suggested algorithm and the mean estimation by a large number of readers. The limit of agreement was narrower than the inter-reader limit of agreement previously reported for the same data. The size of kidney stones is usually estimated manually by the radiologist. An algorithm for computer-aided size estimation is introduced. The variability between readers can be reduced. A reduced variability can give better information for treatment decisions.

Place, publisher, year, edition, pages
New York, USA: Springer, 2012
Keywords
X-ray computed tomography, ureteral calculi, kidney stone, computer-assisted image processing, computer-assisted image interpretation
National Category
Medical and Health Sciences Radiology, Nuclear Medicine and Medical Imaging
Research subject
Medicine
Identifiers
urn:nbn:se:oru:diva-22493 (URN)10.1007/s00330-011-2309-x (DOI)000301496900002 ()22160167 (PubMedID)2-s2.0-84861461077 (Scopus ID)
Note

Funding Agency:

Knowledge Foundation, Stockholm, Sweden 

Available from: 2012-04-10 Created: 2012-04-10 Last updated: 2017-12-07Bibliographically approved
5. Two- and three-dimensional CT measurements of urinary calculi length and width: a comparative study
Open this publication in new window or tab >>Two- and three-dimensional CT measurements of urinary calculi length and width: a comparative study
(English)Manuscript (preprint) (Other academic)
Abstract [en]

The standard imaging procedure for a patient presenting with renal colic is unenhanced CT. The CT measured size has a close correlation to the estimated prognosis for spontaneous passage of a ureteral calculus. Size estimations of urinary calculi in CT images are still based on 2d-reformats. In the present study we developed and validated a calculus oriented 3dmethod for measurements of length and width of urinary calculi and compared those with corresponding 2d measurements in axial and coronal reformats.

Methods: Fifty unenhanced CT examinations demonstrating urinary calculi were included. A 3d-symmetric segmentation algorithm was validated against reader size estimations. The calculus-oriented size from the segmentation was then compared to the size in axial and coronal reformats.

Results: The validation showed 0.1±0.7 mm agreement against reference measure. There was a 0.4 mm median bias for 3d-estimated calculus length compared to 2d (p<0.001), but no significant bias for 3d-width compared to 2d.

Conclusion: The size of the urinary calculus becomes underestimated if its orientation is not aligned to the axial or coronal image plane. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation.

Keywords
3D segmentation; tomography, X-ray computed; image perception; imaging, three- dimensional; image segmentation; image visualization; ureteral calculi; urinary stones; urolithiasis
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Radiology
Identifiers
urn:nbn:se:oru:diva-30364 (URN)
Available from: 2013-08-29 Created: 2013-08-29 Last updated: 2017-10-17Bibliographically approved

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