Gabriel A. Nketiah
St. Olavs Hospital
Trondheim, Norway
Trondheim, Norway
Last Updated: 09/26/2026
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Found 9 publications
Integrating biparametric MRI radiomics with clinical variables improves pre-treatment prediction of prostate cancer recurrence.
Journal: Frontiers in oncology
Published: February 17, 2026
Editorial for "MRI Radiomics-Based Machine Learning for Predict of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions".
Journal: Journal of magnetic resonance imaging : JMRI
Published: May 14, 2021
Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study.
Journal: Scientific reports
Published: September 07, 2020
A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI.
Journal: Diagnostics (Basel, Switzerland)
Published: August 31, 2020
Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition.
Journal: Magma (New York, N.Y.)
Published: April 08, 2020
Geometric distortion correction in prostate diffusion-weighted MRI and its effect on quantitative apparent diffusion coefficient analysis.
Journal: Magnetic resonance in medicine
Published: April 19, 2017
T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.
Journal: European radiology
Published: March 20, 2016
Showing 1-9 of 9
Last Updated: 09/26/2026