Automatic assessment of image informativeness in colonoscopy

Nima Tajbakhsh; Changching Chi; Haripriya Sharma; Qing Wu; Suryakanth R. Gurudu; Jianming Liang

doi:10.1007/978-3-319-13692-9_14

Automatic assessment of image informativeness in colonoscopy

Nima Tajbakhsh, Changching Chi, Haripriya Sharma, Qing Wu, Suryakanth R. Gurudu, Jianming Liang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Scopus citations

Abstract

Optical colonoscopy is the preferred method for colon cancer screening and prevention. The goal of colonoscopy is to find and remove colonic polyps, precursors to colon cancer. However, colonoscopy is not a perfect procedure. Recent clinical studies report a significant polyp miss due to insufficient quality of colonoscopy. To complicate the problem, the existing guidelines for a “good” colonoscopy, such as maintaining a minimum withdrawal time of 6min, are not adequate to guarantee the quality of colonoscopy. In response to this problem, this paper presents a method that can objectively measure the quality of an examination by assessing the informativeness of the corresponding colonoscopy images. By assigning a normalized quality score to each colonoscopy frame, our method can detect the onset of a hasty examination and encourage a more diligent procedure. The computed scores can also be averaged and reported as the overall quality of colonoscopy for quality monitoring purposes. Our experiments reveal that the suggested method achieves higher sensitivity and specificity to non-informative frames than the existing image quality assessment methods for colonoscopy videos.

Original language	English (US)
Title of host publication	Abdominal Imaging
Subtitle of host publication	Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014
Editors	Hiroyuki Yoshida, Janne J. Näppi, Sanjay Saini
Publisher	Springer Verlag
Pages	151-158
Number of pages	8
ISBN (Electronic)	9783319136912
DOIs	https://doi.org/10.1007/978-3-319-13692-9_14
State	Published - Jan 1 2014
Event	6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Cambridge, United States Duration: Sep 14 2014 → Sep 14 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8676
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
Country/Territory	United States
City	Cambridge
Period	9/14/14 → 9/14/14

Keywords

Discrete cosine transform
Image information assessment
Optical colonoscopy
Quality monitoring

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-13692-9_14

Cite this

Tajbakhsh, N., Chi, C., Sharma, H., Wu, Q., Gurudu, S. R., & Liang, J. (2014). Automatic assessment of image informativeness in colonoscopy. In H. Yoshida, J. J. Näppi, & S. Saini (Eds.), Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014 (pp. 151-158). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8676). Springer Verlag. https://doi.org/10.1007/978-3-319-13692-9_14

Automatic assessment of image informativeness in colonoscopy. / Tajbakhsh, Nima; Chi, Changching; Sharma, Haripriya et al.
Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. ed. / Hiroyuki Yoshida; Janne J. Näppi; Sanjay Saini. Springer Verlag, 2014. p. 151-158 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8676).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tajbakhsh, N, Chi, C, Sharma, H, Wu, Q, Gurudu, SR & Liang, J 2014, Automatic assessment of image informativeness in colonoscopy. in H Yoshida, JJ Näppi & S Saini (eds), Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8676, Springer Verlag, pp. 151-158, 6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, Cambridge, United States, 9/14/14. https://doi.org/10.1007/978-3-319-13692-9_14

Tajbakhsh N, Chi C, Sharma H, Wu Q, Gurudu SR, Liang J. Automatic assessment of image informativeness in colonoscopy. In Yoshida H, Näppi JJ, Saini S, editors, Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. Springer Verlag. 2014. p. 151-158. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-13692-9_14

Tajbakhsh, Nima ; Chi, Changching ; Sharma, Haripriya et al. / Automatic assessment of image informativeness in colonoscopy. Abdominal Imaging: Computational and Clinical Applications - 6th International Workshop, ABDI 2014 held in conjunction with MICCAI 2014. editor / Hiroyuki Yoshida ; Janne J. Näppi ; Sanjay Saini. Springer Verlag, 2014. pp. 151-158 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e4717115860c4720af9a89df158d19c6,

title = "Automatic assessment of image informativeness in colonoscopy",

abstract = "Optical colonoscopy is the preferred method for colon cancer screening and prevention. The goal of colonoscopy is to find and remove colonic polyps, precursors to colon cancer. However, colonoscopy is not a perfect procedure. Recent clinical studies report a significant polyp miss due to insufficient quality of colonoscopy. To complicate the problem, the existing guidelines for a “good” colonoscopy, such as maintaining a minimum withdrawal time of 6min, are not adequate to guarantee the quality of colonoscopy. In response to this problem, this paper presents a method that can objectively measure the quality of an examination by assessing the informativeness of the corresponding colonoscopy images. By assigning a normalized quality score to each colonoscopy frame, our method can detect the onset of a hasty examination and encourage a more diligent procedure. The computed scores can also be averaged and reported as the overall quality of colonoscopy for quality monitoring purposes. Our experiments reveal that the suggested method achieves higher sensitivity and specificity to non-informative frames than the existing image quality assessment methods for colonoscopy videos.",

keywords = "Discrete cosine transform, Image information assessment, Optical colonoscopy, Quality monitoring",

author = "Nima Tajbakhsh and Changching Chi and Haripriya Sharma and Qing Wu and Gurudu, {Suryakanth R.} and Jianming Liang",

year = "2014",

month = jan,

day = "1",

doi = "10.1007/978-3-319-13692-9_14",

language = "English (US)",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "151--158",

editor = "Hiroyuki Yoshida and N{\"a}ppi, {Janne J.} and Sanjay Saini",

booktitle = "Abdominal Imaging",

note = "6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 ; Conference date: 14-09-2014 Through 14-09-2014",

}

TY - GEN

T1 - Automatic assessment of image informativeness in colonoscopy

AU - Tajbakhsh, Nima

AU - Chi, Changching

AU - Sharma, Haripriya

AU - Wu, Qing

AU - Gurudu, Suryakanth R.

AU - Liang, Jianming

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Optical colonoscopy is the preferred method for colon cancer screening and prevention. The goal of colonoscopy is to find and remove colonic polyps, precursors to colon cancer. However, colonoscopy is not a perfect procedure. Recent clinical studies report a significant polyp miss due to insufficient quality of colonoscopy. To complicate the problem, the existing guidelines for a “good” colonoscopy, such as maintaining a minimum withdrawal time of 6min, are not adequate to guarantee the quality of colonoscopy. In response to this problem, this paper presents a method that can objectively measure the quality of an examination by assessing the informativeness of the corresponding colonoscopy images. By assigning a normalized quality score to each colonoscopy frame, our method can detect the onset of a hasty examination and encourage a more diligent procedure. The computed scores can also be averaged and reported as the overall quality of colonoscopy for quality monitoring purposes. Our experiments reveal that the suggested method achieves higher sensitivity and specificity to non-informative frames than the existing image quality assessment methods for colonoscopy videos.

AB - Optical colonoscopy is the preferred method for colon cancer screening and prevention. The goal of colonoscopy is to find and remove colonic polyps, precursors to colon cancer. However, colonoscopy is not a perfect procedure. Recent clinical studies report a significant polyp miss due to insufficient quality of colonoscopy. To complicate the problem, the existing guidelines for a “good” colonoscopy, such as maintaining a minimum withdrawal time of 6min, are not adequate to guarantee the quality of colonoscopy. In response to this problem, this paper presents a method that can objectively measure the quality of an examination by assessing the informativeness of the corresponding colonoscopy images. By assigning a normalized quality score to each colonoscopy frame, our method can detect the onset of a hasty examination and encourage a more diligent procedure. The computed scores can also be averaged and reported as the overall quality of colonoscopy for quality monitoring purposes. Our experiments reveal that the suggested method achieves higher sensitivity and specificity to non-informative frames than the existing image quality assessment methods for colonoscopy videos.

KW - Discrete cosine transform

KW - Image information assessment

KW - Optical colonoscopy

KW - Quality monitoring

UR - http://www.scopus.com/inward/record.url?scp=84927608250&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84927608250&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-13692-9_14

DO - 10.1007/978-3-319-13692-9_14

M3 - Conference contribution

AN - SCOPUS:84927608250

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 151

EP - 158

BT - Abdominal Imaging

A2 - Yoshida, Hiroyuki

A2 - Näppi, Janne J.

A2 - Saini, Sanjay

PB - Springer Verlag

T2 - 6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014

Y2 - 14 September 2014 through 14 September 2014

ER -

Automatic assessment of image informativeness in colonoscopy

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this