English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Diffusion weighted magnetic resonance imaging (DW-MR) is a powerful tool inimaging-based prostate cancer screening and detection. Endorectal coils arecommonly used in DW-MR imaging to improve the signal-to-noise ratio (SNR) ofthe acquisition, at the expense of significant intensity inhomogeneities (biasfield) that worsens as we move away from the endorectal coil. The presence ofbias field can have a significant negative impact on the accuracy of differentimage analysis tasks, as well as prostate tumor localization, thus leading toincreased inter- and intra-observer variability. Retrospective bias correctionapproaches are introduced as a more efficient way of bias correction comparedto the prospective methods such that they correct for both of the scanner andanatomy-related bias fields in MR imaging. Previously proposed retrospectivebias field correction methods suffer from undesired noise amplification thatcan reduce the quality of bias-corrected DW-MR image. Here, we propose aunified data reconstruction approach that enables joint compensation of biasfield as well as data noise in DW-MR imaging. The proposed noise-compensated,bias-corrected (NCBC) data reconstruction method takes advantage of a novelstochastically fully connected joint conditional random field (SFC-JCRF) modelto mitigate the effects of data noise and bias field in the reconstructed MRdata. The proposed NCBC reconstruction method was tested on synthetic DW-MRdata, physical DW-phantom as well as real DW-MR data all acquired usingendorectal MR coil. Both qualitative and quantitative analysis illustrated thatthe proposed NCBC method can achieve improved image quality when compared toother tested bias correction methods. As such, the proposed NCBC method mayhave potential as a useful retrospective approach for improving the consistencyof image interpretations.

Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic  Resonance Imaging via a Stochastically Fully-Connected Joint Conditional  Random Field Model