Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization

Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Predict Gleason Score Upgrading in Intermediate-Risk 3 + 4 = 7 Prostate Cancer

(2016) Radu Rozenberg et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

The utility of quantitative ADC values for differentiating high-risk from low-risk prostate cancer: a systematic review and meta-analysis

(2016) Hiram Shaish et al.   Abdominal Radiology

Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review

(2015) Guillaume Lemaître et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

(2015) Andreas Wibmer et al.   EUROPEAN RADIOLOGY

Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice

(2015) Andrew B. Rosenkrantz et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction

(2015) Ivan Jambor et al.   MAGNETIC RESONANCE IN MEDICINE

Relaxation along fictitious field, diffusion-weighted imaging, and T2mapping of prostate cancer: Prediction of cancer aggressiveness

(2015) Ivan Jambor et al.   MAGNETIC RESONANCE IN MEDICINE

Automated prostate cancer detection usingT2-weighted and high-b-value diffusion-weighted magnetic resonance imaging

(2015) Jin Tae Kwak et al.   MEDICAL PHYSICS

Texture features on T2-weighted magnetic resonance imaging: new potential biomarkers for prostate cancer aggressiveness

(2015) A Vignati et al.   PHYSICS IN MEDICINE AND BIOLOGY

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

(2015) Duc Fehr et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

(2015) Erin LeDell et al.   Electronic Journal of Statistics

Regularization Paths for Generalized Linear Models via Coordinate Descent

(2015) Jerome Friedman et al.   Journal of Statistical Software

Correcting for Optimistic Prediction in Small Data Sets

(2014) Gordon C. S. Smith et al.   AMERICAN JOURNAL OF EPIDEMIOLOGY

Apparent diffusion coefficient ratio correlates significantly with prostate cancer gleason score at final pathology

(2014) Lars Boesen et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors

(2014) Shoshana B. Ginsburg et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Mathematical models for diffusion-weighted imaging of prostate cancer using b values up to 2000 s/mm2: Correlation with Gleason score and repeatability of region of interest analysis

(2014) Jussi Toivonen et al.   MAGNETIC RESONANCE IN MEDICINE

Evaluation of different mathematical models for diffusion-weighted imaging of normal prostate and prostate cancer using high b-values: A repeatability study

(2014) Ivan Jambor et al.   MAGNETIC RESONANCE IN MEDICINE

Prostate Cancer Aggressiveness: Assessment with Whole-Lesion Histogram Analysis of the Apparent Diffusion Coefficient

(2014) Olivio F. Donati et al.   RADIOLOGY

scikit-image: image processing in Python

(2014) Stéfan van der Walt et al.   PeerJ

Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities

(2013) Adrien Depeursinge et al.   MEDICAL IMAGE ANALYSIS

Quantitative Analysis of Multiparametric Prostate MR Images: Differentiation between Prostate Cancer and Normal Tissue and Correlation with Gleason Score—A Computer-aided Diagnosis Development Study

(2013) Yahui Peng et al.   RADIOLOGY

Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 tesla endorectal, in vivo T2-weighted MR imagery

(2012) Satish E. Viswanath et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS

(2012) Pallavi Tiwari et al.   MEDICAL IMAGE ANALYSIS

Classification of benign and malignant masses based on Zernike moments

(2011) Amir Tahmasbi et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Local directional derivative pattern for rotation invariant texture classification

(2011) Zhenhua Guo et al.   NEURAL COMPUTING & APPLICATIONS

Prostate Cancer: Multiparametric MR Imaging for Detection, Localization, and Staging

(2011) Caroline M. A. Hoeks et al.   RADIOLOGY

An experimental comparison of cross-validation techniques for estimating the area under the ROC curve

(2010) Antti Airola et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Is Apparent Diffusion Coefficient Associated with Clinical Risk Scores for Prostate Cancers that Are Visible on 3-T MR Images?

(2010) Baris Turkbey et al.   RADIOLOGY

Prostate Cancer Specific Mortality and Gleason 7 Disease Differences in Prostate Cancer Outcomes Between Cases With Gleason 4 + 3 and Gleason 3 + 4 Tumors in a Population Based Cohort

(2009) Jonathan L. Wright et al.   JOURNAL OF UROLOGY

An Update of the Gleason Grading System

(2009) Jonathan I. Epstein   JOURNAL OF UROLOGY

Gleason score and laterality concordance between prostate biopsy and prostatectomy specimens

(2009) Kenneth G. Nepple et al.   International Braz J Urol

Apparent diffusion coefficient values in peripheral and transition zones of the prostate: Comparison between normal and malignant prostatic tissues and correlation with histologic grade

(2008) Tsutomu Tamada et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Robust reductions from ranking to classification

(2008) Maria-Florina Balcan et al.   MACHINE LEARNING

Trends in Gleason Score: Concordance Between Biopsy and Prostatectomy over 15 Years

(2008) Ayyathurai Rajinikanth et al.   UROLOGY