Detalhe da pesquisa
1.
The impact of pre-processing and disease characteristics on reproducibility of T2-weighted MRI radiomics features.
MAGMA
; 36(6): 945-956, 2023 Dec.
Artigo
em Inglês
| MEDLINE | ID: mdl-37556085
2.
Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition.
MAGMA
; 34(2): 309-321, 2021 Apr.
Artigo
em Inglês
| MEDLINE | ID: mdl-32737628
3.
Geometric distortion correction in prostate diffusion-weighted MRI and its effect on quantitative apparent diffusion coefficient analysis.
Magn Reson Med
; 79(5): 2524-2532, 2018 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-28862352
4.
T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.
Eur Radiol
; 27(7): 3050-3059, 2017 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-27975146
5.
Editorial for "MRI Radiomics-Based Machine Learning for Predict of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions".
J Magn Reson Imaging
; 54(5): 1474-1475, 2021 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-34046969
6.
Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study.
Sci Rep
; 11(1): 2085, 2021 01 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-33483545
7.
A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI.
Diagnostics (Basel)
; 10(9)2020 Sep 18.
Artigo
em Inglês
| MEDLINE | ID: mdl-32961895