A maximum-likelihood approach for ADC estimation of lesions in visceral organs

Abhinav K. Jha, Jeffrey J Rodriguez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
Pages21-24
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012 - Santa Fe, NM, United States
Duration: Apr 22 2012Apr 24 2012

Other

Other2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012
CountryUnited States
CitySanta Fe, NM
Period4/22/124/24/12

Fingerprint

Maximum likelihood
Magnetic resonance
Linear regression
Imaging techniques

Keywords

  • ADC estimation
  • Maximum-likelihood method
  • Mean of Rician distributed random variables

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Jha, A. K., & Rodriguez, J. J. (2012). A maximum-likelihood approach for ADC estimation of lesions in visceral organs. In Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation (pp. 21-24). [6202443] https://doi.org/10.1109/SSIAI.2012.6202443

A maximum-likelihood approach for ADC estimation of lesions in visceral organs. / Jha, Abhinav K.; Rodriguez, Jeffrey J.

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation. 2012. p. 21-24 6202443.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jha, AK & Rodriguez, JJ 2012, A maximum-likelihood approach for ADC estimation of lesions in visceral organs. in Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation., 6202443, pp. 21-24, 2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012, Santa Fe, NM, United States, 4/22/12. https://doi.org/10.1109/SSIAI.2012.6202443
Jha AK, Rodriguez JJ. A maximum-likelihood approach for ADC estimation of lesions in visceral organs. In Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation. 2012. p. 21-24. 6202443 https://doi.org/10.1109/SSIAI.2012.6202443
Jha, Abhinav K. ; Rodriguez, Jeffrey J. / A maximum-likelihood approach for ADC estimation of lesions in visceral organs. Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation. 2012. pp. 21-24
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