TY - GEN
T1 - 3D blob based brain tumor detection and segmentation in MR images
AU - Yu, Chen Ping
AU - Ruppert, Guilherme
AU - Collins, Robert
AU - Nguyen, Dan
AU - Falcao, Alexandre
AU - Liu, Yanxi
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/7/29
Y1 - 2014/7/29
N2 - Automatic detection and segmentation of brain tumors in 3D MR neuroimages can significantly aid early diagnosis, surgical planning, and follow-up assessment. However, due to diverse location and varying size, primary and metastatic tumors present substantial challenges for detection. We present a fully automatic, unsupervised algorithm that can detect single and multiple tumors from 3 to 28, 079 mm3 in volume. Using 20 clinical 3D MR scans containing from 1 to 15 tumors per scan, the proposed approach achieves between 87.84% and 95.30% detection rate and an average end-to-end running time of under 3 minutes. In addition, 5 normal clinical 3D MR scans are evaluated quantitatively to demonstrate that the approach has the potential to discriminate between abnormal and normal brains.
AB - Automatic detection and segmentation of brain tumors in 3D MR neuroimages can significantly aid early diagnosis, surgical planning, and follow-up assessment. However, due to diverse location and varying size, primary and metastatic tumors present substantial challenges for detection. We present a fully automatic, unsupervised algorithm that can detect single and multiple tumors from 3 to 28, 079 mm3 in volume. Using 20 clinical 3D MR scans containing from 1 to 15 tumors per scan, the proposed approach achieves between 87.84% and 95.30% detection rate and an average end-to-end running time of under 3 minutes. In addition, 5 normal clinical 3D MR scans are evaluated quantitatively to demonstrate that the approach has the potential to discriminate between abnormal and normal brains.
UR - http://www.scopus.com/inward/record.url?scp=84927945311&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84927945311&partnerID=8YFLogxK
U2 - 10.1109/isbi.2014.6868089
DO - 10.1109/isbi.2014.6868089
M3 - Conference contribution
AN - SCOPUS:84927945311
T3 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
SP - 1192
EP - 1197
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 -