Apparent diffusion coefficient estimation in prostate DW-MRI using maximum likelihood.
Presented at: ISMRM 2012, Melbourne, Australia.
The problem of apparent diffusion coefficient (ADC) estimation from Rician distributed diffusion-weighted magnetic resonance (DW-MR) data is addressed. The least squares (LS) algorithm, widely used in clinical practice, is known to produce biased estimates as it considers the noise as normally distributed. Maximum likelihood (ML) can provide a more robust alternative. In this study based on prostate cancer DW-MR, we compared LS and ML efficiency, for signal to noise ratios typical of the different types of tissue. The ML approach provided significantly less biased estimates than the LS, potentially allowing better accuracy in prostate cancer grading from MR images.
|Type:||Conference item (UNSPECIFIED)|
|Title:||Apparent diffusion coefficient estimation in prostate DW-MRI using maximum likelihood|
|Dates:||07 May 2012 - 12 May 2012|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Medical Sciences > Medicine (Division of)
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