MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection

BMC Medical Imaging
Farzad KhalvatiMasoom A Haider

Abstract

Quantitative radiomic features provide a plethora of minable data extracted from multi-parametric magnetic resonance imaging (MP-MRI) which can be used for accurate detection and localization of prostate cancer. While most cancer detection algorithms utilize either voxel-based or region-based feature models, the complexity of prostate tumour phenotype in MP-MRI requires a more sophisticated framework to better leverage available data and exploit a priori knowledge in the field. In this paper, we present MPCaD, a novel Multi-scale radiomics-driven framework for Prostate Cancer Detection and localization which leverages radiomic feature models at different scales as well as incorporates a priori knowledge of the field. Tumour candidate localization is first performed using a statistical texture distinctiveness strategy that leverages a voxel-resolution feature model to localize tumour candidate regions. Tumour region classification via a region-resolution feature model is then performed to identify tumour regions. Both voxel-resolution and region-resolution feature models are built upon and extracted from six different MP-MRI modalities. Finally, a conditional random field framework that is driven by voxel-resolution relative ADC...Continue Reading

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Citations

Jul 11, 2020·Strahlentherapie und Onkologie : Organ der Deutschen Röntgengesellschaft ... [et al]·Philipp LohmannHarald Treuer
Dec 22, 2019·Scientific Reports·Sunghwan YooFarzad Khalvati
Jul 20, 2019·Molecular Imaging and Biology : MIB : the Official Publication of the Academy of Molecular Imaging·Shuai MaXiaodong Zhang
May 7, 2021·AJR. American Journal of Roentgenology·Huiping ZhaoJianbo Gao
Jun 13, 2020·European Journal of Radiology·Arnaldo StanzioneMassimo Imbriaco
Aug 24, 2021·Nihon Hoshasen Gijutsu Gakkai zasshi·Koji Sakai
Aug 31, 2021·Journal of Imaging·Giuseppe CutaiaGiuseppe Salvaggio

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Methods Mentioned

BETA
biopsy
biopsies
feature extraction

Software Mentioned

RD
CRF
ProCanVAS ( Prostate Cancer Visualization and Analysis System )
MP
MPCaD
Radiomics
RADS
FM
STD
PI

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