TY - GEN
T1 - Liver tumor detection in CT images by adaptive contrast enhancement and the EM/MPM algorithm
AU - Masuda, Yu
AU - Tateyama, Tomoko
AU - Xiong, Wei
AU - Zhou, Jiayin
AU - Wakamiya, Makoto
AU - Kanasaki, Syuzo
AU - Furukawa, Akira
AU - Chen, Yen Wei
PY - 2011
Y1 - 2011
N2 - Automatic tumor detection and segmentation is essential for the computer-aided diagnosis of live tumors in CT images. However, it is a challenging task in low-contrast images as the low-level images are too weak to detect. In this paper, we propose a new method for the automatic detection of liver tumors. We first adaptively enhance the intensity contrast of CT images by probability density function estimation. Then, to detect tumorous regions, we use the expectation maximization/maximization of the posterior marginal (EM/MPM) algorithm, which utilizes both the intensity and label information of the adjacent regions. Finally, a shape constraint is applied to reduce noise and identify focal tumors. Quantitative evaluation experiments show that our method can accurately and effectively detect tumors even in poor-contrast CT images.
AB - Automatic tumor detection and segmentation is essential for the computer-aided diagnosis of live tumors in CT images. However, it is a challenging task in low-contrast images as the low-level images are too weak to detect. In this paper, we propose a new method for the automatic detection of liver tumors. We first adaptively enhance the intensity contrast of CT images by probability density function estimation. Then, to detect tumorous regions, we use the expectation maximization/maximization of the posterior marginal (EM/MPM) algorithm, which utilizes both the intensity and label information of the adjacent regions. Finally, a shape constraint is applied to reduce noise and identify focal tumors. Quantitative evaluation experiments show that our method can accurately and effectively detect tumors even in poor-contrast CT images.
UR - http://www.scopus.com/inward/record.url?scp=84863055750&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863055750&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2011.6115708
DO - 10.1109/ICIP.2011.6115708
M3 - Conference contribution
AN - SCOPUS:84863055750
SN - 9781457713033
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1421
EP - 1424
BT - ICIP 2011
T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011
Y2 - 11 September 2011 through 14 September 2011
ER -