Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning

Derek Burrows; Chad Washington; Ralph Dacey; Tao Ju

doi:10.1109/isbi.2014.6868118

Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning

Derek Burrows, Chad Washington, Ralph Dacey, Tao Ju

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

Abstract

We present a method for classifying the shape of middle cerebral artery (MCA) aneurysms using segmented surfaces from angiograms. The classification follows a set of visual criteria established by experienced surgeons to group aneurysms based on the clipping strategies used in surgery. Starting from a centerline representation of the input, our method automatically classifies the input into one of 4 types using a combination of graph analysis and supervised learning. When evaluated on a cohort of 84 subjects, our method achieves between 60% to 69% expected classification accuracy (p < 10^-3) with zero to a moderate amount of input from novice users.

Original language	English
Title of host publication	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1311-1315
Number of pages	5
ISBN (Electronic)	9781467319591
DOIs	https://doi.org/10.1109/isbi.2014.6868118
State	Published - Jul 29 2014
Event	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China Duration: Apr 29 2014 → May 2 2014

Publication series

Name	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Conference

Conference	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/Territory	China
City	Beijing
Period	04/29/14 → 05/2/14

Access to Document

10.1109/isbi.2014.6868118

Cite this

Burrows, D., Washington, C., Dacey, R., & Ju, T. (2014). Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 1311-1315). Article 6868118 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/isbi.2014.6868118

Burrows, Derek ; Washington, Chad ; Dacey, Ralph et al. / Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning. 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 1311-1315 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014).

@inproceedings{591cd16ae8534e21bd7c63d39d92e186,

title = "Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning",

abstract = "We present a method for classifying the shape of middle cerebral artery (MCA) aneurysms using segmented surfaces from angiograms. The classification follows a set of visual criteria established by experienced surgeons to group aneurysms based on the clipping strategies used in surgery. Starting from a centerline representation of the input, our method automatically classifies the input into one of 4 types using a combination of graph analysis and supervised learning. When evaluated on a cohort of 84 subjects, our method achieves between 60% to 69% expected classification accuracy (p < 10-3) with zero to a moderate amount of input from novice users.",

author = "Derek Burrows and Chad Washington and Ralph Dacey and Tao Ju",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 ; Conference date: 29-04-2014 Through 02-05-2014",

year = "2014",

month = jul,

day = "29",

doi = "10.1109/isbi.2014.6868118",

language = "English",

series = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1311--1315",

booktitle = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014",

}

Burrows, D, Washington, C, Dacey, R & Ju, T 2014, Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6868118, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 1311-1315, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China, 04/29/14. https://doi.org/10.1109/isbi.2014.6868118

Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning. / Burrows, Derek; Washington, Chad; Dacey, Ralph et al.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1311-1315 6868118 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014).

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

TY - GEN

T1 - Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning

AU - Burrows, Derek

AU - Washington, Chad

AU - Dacey, Ralph

AU - Ju, Tao

PY - 2014/7/29

Y1 - 2014/7/29

N2 - We present a method for classifying the shape of middle cerebral artery (MCA) aneurysms using segmented surfaces from angiograms. The classification follows a set of visual criteria established by experienced surgeons to group aneurysms based on the clipping strategies used in surgery. Starting from a centerline representation of the input, our method automatically classifies the input into one of 4 types using a combination of graph analysis and supervised learning. When evaluated on a cohort of 84 subjects, our method achieves between 60% to 69% expected classification accuracy (p < 10-3) with zero to a moderate amount of input from novice users.

AB - We present a method for classifying the shape of middle cerebral artery (MCA) aneurysms using segmented surfaces from angiograms. The classification follows a set of visual criteria established by experienced surgeons to group aneurysms based on the clipping strategies used in surgery. Starting from a centerline representation of the input, our method automatically classifies the input into one of 4 types using a combination of graph analysis and supervised learning. When evaluated on a cohort of 84 subjects, our method achieves between 60% to 69% expected classification accuracy (p < 10-3) with zero to a moderate amount of input from novice users.

UR - http://www.scopus.com/inward/record.url?scp=84927925334&partnerID=8YFLogxK

U2 - 10.1109/isbi.2014.6868118

DO - 10.1109/isbi.2014.6868118

M3 - Conference contribution

AN - SCOPUS:84927925334

T3 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

SP - 1311

EP - 1315

BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Y2 - 29 April 2014 through 2 May 2014

ER -

Burrows D, Washington C, Dacey R , Ju T. Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1311-1315. 6868118. (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). doi: 10.1109/isbi.2014.6868118

Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this