TY - GEN
T1 - A maximum-likelihood approach for ADC estimation of lesions in visceral organs
AU - Jha, Abhinav K.
AU - Rodríguez, Jeffrey J.
PY - 2012
Y1 - 2012
N2 - Accurate estimation of the apparent diffusion coefficient (ADC) of lesions in diffusion-weighted magnetic resonance imaging (DWMRI) is important to predict and monitor anticancer therapy response. The task of ADC estimation of lesions is complicated due to noise in the image, different variances in signal strengths at different b values and other random phenomena. In organs that have visceral motion, due to motion across scans, estimating the ADC becomes even more complex. To get rid of inaccuracies due to motion, only a single ADC value of the lesion is estimated, conventionally using a linear-regression (LR) approach. The LR approach is based on an inaccurate noise model and also suffers from other deficiencies. In this paper, we propose an easy-to-implement and computationally-fast maximum-likelihood (ML) method to estimate the ADC value of heterogeneous lesions in visceral organs. The proposed method takes into account the Rician distribution of noise in DWMRI. In the process, we also derive the statistical model for the measured mean signal intensity in DWMRI. We show using Monte-Carlo simulations that that the proposed method is more accurate than the LR method.
AB - Accurate estimation of the apparent diffusion coefficient (ADC) of lesions in diffusion-weighted magnetic resonance imaging (DWMRI) is important to predict and monitor anticancer therapy response. The task of ADC estimation of lesions is complicated due to noise in the image, different variances in signal strengths at different b values and other random phenomena. In organs that have visceral motion, due to motion across scans, estimating the ADC becomes even more complex. To get rid of inaccuracies due to motion, only a single ADC value of the lesion is estimated, conventionally using a linear-regression (LR) approach. The LR approach is based on an inaccurate noise model and also suffers from other deficiencies. In this paper, we propose an easy-to-implement and computationally-fast maximum-likelihood (ML) method to estimate the ADC value of heterogeneous lesions in visceral organs. The proposed method takes into account the Rician distribution of noise in DWMRI. In the process, we also derive the statistical model for the measured mean signal intensity in DWMRI. We show using Monte-Carlo simulations that that the proposed method is more accurate than the LR method.
KW - ADC estimation
KW - Maximum-likelihood method
KW - Mean of Rician distributed random variables
UR - http://www.scopus.com/inward/record.url?scp=84862750200&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862750200&partnerID=8YFLogxK
U2 - 10.1109/SSIAI.2012.6202443
DO - 10.1109/SSIAI.2012.6202443
M3 - Conference contribution
C2 - 25242901
AN - SCOPUS:84862750200
SN - 9781467318303
T3 - Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
SP - 21
EP - 24
BT - 2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012, Proceedings
T2 - 2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012
Y2 - 22 April 2012 through 24 April 2012
ER -