| 1. |
- Lidén, Mats, 1976-, et al.
(author)
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Two- and three-dimensional CT measurements of urinary calculi length and width : a comparative study
- 2015
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In: Acta Radiologica. - : Sage Publications. - 0284-1851 .- 1600-0455. ; 56:4, s. 487-492
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Journal article (peer-reviewed)abstract
- Background: The standard imaging procedure for a patient presenting with renal colic is unenhanced computed tomography (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 two-dimensional (2D) reformats.Purpose: To develop and validate a calculus oriented three-dimensional (3D) method for measuring the length and width of urinary calculi and to compare the calculus oriented measurements of the length and width with corresponding 2D measurements obtained in axial and coronal reformats.Material and 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 estimated size in axial and coronal 2D reformats.Results: The validation showed 0.1 +/- 0.7mm agreement against reference measure. There was a 0.4mm 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 length of a calculus in axial and coronal reformats becomes underestimated compared to 3D if its orientation is not aligned to the image planes. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation.
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| 2. |
- Broxvall, Mathias, 1976-, et al.
(author)
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Developing Medical Image Processing Algorithms for GPU assisted parallel computation
- 2013
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In: Computer Vision in Medical Imaging. - : World Scientific. - 9789814460934 - 9789814460958 ; , s. 245-270
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Book chapter (peer-reviewed)abstract
- GPU’s have recently emerged as a significantly more powerful computing plat-form, capable of several orders of magnitude faster computations compared toCPU based approaches. However, they require significant changes in the algorithmic design compared to traditional programming paradigms. In this chapter we specifically introduce the reader to an overview of GPGPU development tools and the potential algorithmic pitfalls and bottlenecks when developing medical imaging algorithms for the GPU. We present a few general methodologies and building blocks for implementing fast image processing on GPUs. More specifically they include: methods for performing fast image convolutions and filtering;line detection, and bandwidth and memory considerations when processing volumetric datasets. Finally we conclude with a discourse on numerical precision as well as on mixing single floating-point versus double floating-point code.
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| 3. |
- Lidén, Mats, 1976-, et al.
(author)
-
Two- and three-dimensional CT measurements of urinary calculi length and width : a comparative study
-
Other publication (other academic/artistic)abstract
- 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.
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| 4. |
- Lidén, Mats, 1976-, et al.
(author)
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Urinary stone size estimation : a new segmentation algorithm-based CT method
- 2012
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In: European Radiology. - New York, USA : Springer. - 0938-7994 .- 1432-1084. ; 22:4, s. 731-737
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Journal article (peer-reviewed)abstract
- 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.
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