Vis enkel innførsel

dc.contributor.authorSunoqrot, Mohammed R. S.
dc.contributor.authorNketiah, Gabriel Addio
dc.contributor.authorSelnæs, Kirsten Margrete
dc.contributor.authorBathen, Tone Frost
dc.contributor.authorElschot, Mattijs
dc.identifier.citationMagnetic Resonance Materials in Physics, Biology and Medicine. 2020, .en_US
dc.description.abstractObjectives To develop and evaluate an automated method for prostate T2-weighted (T2W) image normalization using dual-reference (fat and muscle) tissue. Materials and methods Transverse T2W images from the publicly available PROMISE12 (N = 80) and PROSTATEx (N = 202) challenge datasets, and an in-house collected dataset (N = 60) were used. Aggregate channel features object detectors were trained to detect reference fat and muscle tissue regions, which were processed and utilized to normalize the 3D images by linear scaling. Mean prostate pseudo T2 values after normalization were compared to literature values. Inter-patient histogram intersections of voxel intensities in the prostate were compared between our approach, the original images, and other commonly used normalization methods. Healthy vs. malignant tissue classification performance was compared before and after normalization. Results The prostate pseudo T2 values of the three tested datasets (mean ± standard deviation = 78.49 ± 9.42, 79.69 ± 6.34 and 79.29 ± 6.30 ms) corresponded well to T2 values from literature (80 ± 34 ms). Our normalization approach resulted in significantly higher (p < 0.001) inter-patient histogram intersections (median = 0.746) than the original images (median = 0.417) and most other normalization methods. Healthy vs. malignant classification also improved significantly (p < 0.001) in peripheral (AUC 0.826 vs. 0.769) and transition (AUC 0.743 vs. 0.678) zones. Conclusion An automated dual-reference tissue normalization of T2W images could help improve the quantitative assessment of prostate cancer.en_US
dc.publisherSpringer Natureen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleAutomated reference tissue normalization of T2-weighted MR images of the prostate using object recognitionen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalMagnetic Resonance Materials in Physics, Biology and Medicineen_US
dc.description.localcodeOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit

Tilhørende fil(er)


Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Navngivelse 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Navngivelse 4.0 Internasjonal