TY - GEN
T1 - Liver segmentation in contrast enhanced MR datasets using a probabilistic active shape and appearance model
AU - Drechsler, Klaus
AU - Knaub, Anton
AU - Laura, Cristina Oyarzun
AU - Wesarg, Stefan
PY - 2014
Y1 - 2014
N2 - The current standard for diagnosing liver tumors is contrast-enhanced multiphase computed tomography. On this basis, several software tools have been developed by different research groups worldwide to support physicians for example in measuring remnant liver volume, analyzing tumors, and planning resections. Several algorithms have been developed to perform these tasks. Most of the time, the segmentation of the liver is at the beginning of the processing chain. Therefore, a vast amount of CT-based liver segmentation algorithms have been developed. However, clinics slowly move from CT as the current gold standard for diagnosing liver diseases towards magnetic resonance imaging. In this work, we utilize a Probabilistic Active Shape Model with an MR specific preprocessing and appearance model to segment the liver in contrast enhanced MR images. Evaluation is based on 8 clinical datasets.
AB - The current standard for diagnosing liver tumors is contrast-enhanced multiphase computed tomography. On this basis, several software tools have been developed by different research groups worldwide to support physicians for example in measuring remnant liver volume, analyzing tumors, and planning resections. Several algorithms have been developed to perform these tasks. Most of the time, the segmentation of the liver is at the beginning of the processing chain. Therefore, a vast amount of CT-based liver segmentation algorithms have been developed. However, clinics slowly move from CT as the current gold standard for diagnosing liver diseases towards magnetic resonance imaging. In this work, we utilize a Probabilistic Active Shape Model with an MR specific preprocessing and appearance model to segment the liver in contrast enhanced MR images. Evaluation is based on 8 clinical datasets.
UR - http://www.scopus.com/inward/record.url?scp=84907421052&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2014.120
DO - 10.1109/CBMS.2014.120
M3 - Conference contribution
AN - SCOPUS:84907421052
SN - 9781479944354
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 523
EP - 524
BT - Proceedings - 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, CBMS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2014
Y2 - 27 May 2014 through 29 May 2014
ER -