Bootstrap coverage plots for image segmentation

Inge Koch; Gary Marshall

doi:10.1109/ICPR.1996.546865

Bootstrap coverage plots for image segmentation

Inge Koch, Gary Marshall

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

11 Citations (Scopus)

Abstract

Two methods for assessing the variability of image segmentation are proposed: coverage plots and percentile intervals. Both methods are based on bootstrap techniques and provide graphical information about the performance and accuracy of segmentation methods across the entire image. The methods are applied to median based image segmentation which is characterised by the filter size and a data-driven thresholding choice. Computer simulations of simulated medical X-ray images demonstrate the superiority of coverage plots in assessing the performance of segmentation methods.

Original language	English
Title of host publication	Proceedings of 13th International Conference on Pattern Recognition
Subtitle of host publication	Track B: Pattern Recognition and Signal Analysis
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	447-451
Number of pages	5
Volume	2
ISBN (Print)	081867282X, 9780818672828
DOIs	https://doi.org/10.1109/ICPR.1996.546865
Publication status	Published - 1 Jan 1996
Externally published	Yes
Event	13th International Conference on Pattern Recognition - Vienna, Austria Duration: 25 Aug 1996 → 29 Aug 1996

Conference

Conference	13th International Conference on Pattern Recognition
Abbreviated title	ICPR 1996
Country/Territory	Austria
City	Vienna
Period	25/08/96 → 29/08/96

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10.1109/ICPR.1996.546865

Cite this

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title = "Bootstrap coverage plots for image segmentation",

abstract = "Two methods for assessing the variability of image segmentation are proposed: coverage plots and percentile intervals. Both methods are based on bootstrap techniques and provide graphical information about the performance and accuracy of segmentation methods across the entire image. The methods are applied to median based image segmentation which is characterised by the filter size and a data-driven thresholding choice. Computer simulations of simulated medical X-ray images demonstrate the superiority of coverage plots in assessing the performance of segmentation methods.",

author = "Inge Koch and Gary Marshall",

year = "1996",

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doi = "10.1109/ICPR.1996.546865",

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note = "13th International Conference on Pattern Recognition, ICPR 1996 ; Conference date: 25-08-1996 Through 29-08-1996",

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Koch, I & Marshall, G 1996, Bootstrap coverage plots for image segmentation. in Proceedings of 13th International Conference on Pattern Recognition: Track B: Pattern Recognition and Signal Analysis. vol. 2, 546865, IEEE, Institute of Electrical and Electronics Engineers, pp. 447-451, 13th International Conference on Pattern Recognition, Vienna, Austria, 25/08/96. https://doi.org/10.1109/ICPR.1996.546865

Bootstrap coverage plots for image segmentation. / Koch, Inge; Marshall, Gary.
Proceedings of 13th International Conference on Pattern Recognition: Track B: Pattern Recognition and Signal Analysis. Vol. 2 IEEE, Institute of Electrical and Electronics Engineers, 1996. p. 447-451 546865.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

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AU - Koch, Inge

AU - Marshall, Gary

PY - 1996/1/1

Y1 - 1996/1/1

N2 - Two methods for assessing the variability of image segmentation are proposed: coverage plots and percentile intervals. Both methods are based on bootstrap techniques and provide graphical information about the performance and accuracy of segmentation methods across the entire image. The methods are applied to median based image segmentation which is characterised by the filter size and a data-driven thresholding choice. Computer simulations of simulated medical X-ray images demonstrate the superiority of coverage plots in assessing the performance of segmentation methods.

AB - Two methods for assessing the variability of image segmentation are proposed: coverage plots and percentile intervals. Both methods are based on bootstrap techniques and provide graphical information about the performance and accuracy of segmentation methods across the entire image. The methods are applied to median based image segmentation which is characterised by the filter size and a data-driven thresholding choice. Computer simulations of simulated medical X-ray images demonstrate the superiority of coverage plots in assessing the performance of segmentation methods.

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U2 - 10.1109/ICPR.1996.546865

DO - 10.1109/ICPR.1996.546865

M3 - Conference paper

AN - SCOPUS:0346387900

SN - 081867282X

SN - 9780818672828

VL - 2

SP - 447

EP - 451

BT - Proceedings of 13th International Conference on Pattern Recognition

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 13th International Conference on Pattern Recognition

Y2 - 25 August 1996 through 29 August 1996

ER -

Bootstrap coverage plots for image segmentation

Abstract

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