| T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results G Nketiah, M Elschot, E Kim, JR Teruel, TW Scheenen, TF Bathen, ... European radiology 27, 3050-3059, 2017 | 151 | 2017 |
| Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition MRS Sunoqrot, GA Nketiah, KM Selnæs, TF Bathen, M Elschot Magnetic Resonance Materials in Physics, Biology and Medicine 34, 309-321, 2021 | 27 | 2021 |
| A quality control system for automated prostate segmentation on T2-weighted MRI MRS Sunoqrot, KM Selnæs, E Sandsmark, GA Nketiah, O Zavala-Romero, ... Diagnostics 10 (9), 714, 2020 | 27 | 2020 |
| Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study GA Nketiah, M Elschot, TW Scheenen, MC Maas, TF Bathen, KM Selnæs Scientific reports 11 (1), 2085, 2021 | 21 | 2021 |
| Detection of exercise load‐associated differences in hip muscles by texture analysis G Nketiah, S Savio, P Dastidar, R Nikander, H Eskola, H Sievänen Scandinavian journal of medicine & science in sports 25 (3), 428-434, 2015 | 18 | 2015 |
| Geometric distortion correction in prostate diffusion‐weighted MRI and its effect on quantitative apparent diffusion coefficient analysis G Nketiah, KM Selnæs, E Sandsmark, JR Teruel, B Krüger‐Stokke, ... Magnetic Resonance in Medicine 79 (5), 2524-2532, 2018 | 17 | 2018 |
| The impact of pre-processing and disease characteristics on reproducibility of T2-weighted MRI radiomics features DEO Dewi, MRS Sunoqrot, GA Nketiah, E Sandsmark, GF Giskeødegård, ... Magnetic Resonance Materials in Physics, Biology and Medicine 36 (6), 945-956, 2023 | 2 | 2023 |
| Editorial for" MRI Radiomics-Based Machine Learning for Predict of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions". GA Nketiah, TF Bathen Journal of Magnetic Resonance Imaging: JMRI 54 (5), 1474-1475, 2021 | 2 | 2021 |
| Evaluation of T2W MRI-Derived Textural Entropy for Assessment of Prostate Cancer Aggressiveness G Nketiah, M Elschot, E Kim, TF Bathen, KM Selnæs ISMRM: Concord, CA, USA, 2016 | 1 | 2016 |
| Correlation between hip muscles MRI texture parameters and femoral neck boneareal bone mineral density (aBMD) in different athletes groups G Nketiah, H Sievanen, H Eskola Physica Medica: European Journal of Medical Physics 30, e38-e39, 2014 | 1 | 2014 |
| Computer-Aided Diagnosis of Prostate Cancer Using Multiparametric MRI: Preprocessing, Segmentation and Quality Control MRS Sunoqrot NTNU, 2021 | | 2021 |
| Magnetic Resonance Imaging for Improved Prostate Cancer Diagnosis GA Nketiah NTNU, 2018 | | 2018 |
| Comparison of 2D and 3D MRI Texture Analyses of Functionally Different Hip Muscles G Nketiah | | 2013 |
| Object Recognition for Fully Automated Reference Tissue Normalization of T2-weighted MR Images of the Prostate M Elschot, GA Nketiah, MRS Sunoqrot, TF Bathen | | |
| T2-weighted MRI-derived textural features can help the assessment of peripheral zone prostate cancer aggressiveness: results from multi-center data. G Nketiah, M Elschot, TW Scheenen, MC Maas, TF Bathen, KM Selnæs | | |
| mpMRI-based Tumor Probability Maps for Guidance of Targeted Prostate Biopsies GA Nketiah, N Bakx, KM Selnæs, AL Breto, R Stoyanova, M Elschot, ... | | |
| Added Value of DCE in Machine Learning-based Tumor Probability Maps for Predicting Clinically Significant Cancer Foci in Pre-biopsy MR images GA Nketiah, L Pallas, AL Breto, R Stoyanova, M Elschot, TF Bathen | | |
| Geometric Distortion Correction of Diffusion-Weighted MRI and its Effect on quantitative ADC analysis G Nketiah, KM Selnæs, E Sandsmark, JR Teruel, TF Bathen, M Elschot | | |
| Developing a Delta Radiomics Framework for Prostate Cancer Progression Biomarkers in Patients under Active Surveillance: Pilot Study DEO Dewi, MRS Sunoqrot, GA Nketiah, E Sandsmark, S Langørgen, ... | | |
| A deep learning-based quality control system for co-registration of prostate MR images MRS Sunoqrot, KM Selnæs, BS Abrahamsen, A Patsanis, GA Nketiah, ... | | |
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