313 related articles for article (PubMed ID: 31283771)
1. Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization.
Toivonen J; Montoya Perez I; Movahedi P; Merisaari H; Pesola M; Taimen P; Boström PJ; Pohjankukka J; Kiviniemi A; Pahikkala T; Aronen HJ; Jambor I
PLoS One; 2019; 14(7):e0217702. PubMed ID: 31283771
[TBL] [Abstract][Full Text] [Related]
2. Radiomics Features Measured with Multiparametric Magnetic Resonance Imaging Predict Prostate Cancer Aggressiveness.
Hectors SJ; Cherny M; Yadav KK; Beksaç AT; Thulasidass H; Lewis S; Davicioni E; Wang P; Tewari AK; Taouli B
J Urol; 2019 Sep; 202(3):498-505. PubMed ID: 30958743
[TBL] [Abstract][Full Text] [Related]
3. Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer.
Bleker J; Kwee TC; Dierckx RAJO; de Jong IJ; Huisman H; Yakar D
Eur Radiol; 2020 Mar; 30(3):1313-1324. PubMed ID: 31776744
[TBL] [Abstract][Full Text] [Related]
4. Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models.
Khalvati F; Wong A; Haider MA
BMC Med Imaging; 2015 Aug; 15():27. PubMed ID: 26242589
[TBL] [Abstract][Full Text] [Related]
5. Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings.
Shiradkar R; Ghose S; Jambor I; Taimen P; Ettala O; Purysko AS; Madabhushi A
J Magn Reson Imaging; 2018 Dec; 48(6):1626-1636. PubMed ID: 29734484
[TBL] [Abstract][Full Text] [Related]
6. Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.
Abdollahi H; Mofid B; Shiri I; Razzaghdoust A; Saadipoor A; Mahdavi A; Galandooz HM; Mahdavi SR
Radiol Med; 2019 Jun; 124(6):555-567. PubMed ID: 30607868
[TBL] [Abstract][Full Text] [Related]
7. Evaluation of Diffusion Kurtosis Imaging Versus Standard Diffusion Imaging for Detection and Grading of Peripheral Zone Prostate Cancer.
Roethke MC; Kuder TA; Kuru TH; Fenchel M; Hadaschik BA; Laun FB; Schlemmer HP; Stieltjes B
Invest Radiol; 2015 Aug; 50(8):483-9. PubMed ID: 25867657
[TBL] [Abstract][Full Text] [Related]
8. Automatic stratification of prostate tumour aggressiveness using multiparametric MRI: a horizontal comparison of texture features.
Sun Y; Reynolds HM; Wraith D; Williams S; Finnegan ME; Mitchell C; Murphy D; Haworth A
Acta Oncol; 2019 Aug; 58(8):1118-1126. PubMed ID: 30994052
[No Abstract] [Full Text] [Related]
9. MRI-based texture analysis of the primary tumor for pre-treatment prediction of bone metastases in prostate cancer.
Wang Y; Yu B; Zhong F; Guo Q; Li K; Hou Y; Lin N
Magn Reson Imaging; 2019 Jul; 60():76-84. PubMed ID: 30917943
[TBL] [Abstract][Full Text] [Related]
10. Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.
Ginsburg SB; Algohary A; Pahwa S; Gulani V; Ponsky L; Aronen HJ; Boström PJ; Böhm M; Haynes AM; Brenner P; Delprado W; Thompson J; Pulbrock M; Taimen P; Villani R; Stricker P; Rastinehad AR; Jambor I; Madabhushi A
J Magn Reson Imaging; 2017 Jul; 46(1):184-193. PubMed ID: 27990722
[TBL] [Abstract][Full Text] [Related]
11. Exploring the efficacy of multi-flavored feature extraction with radiomics and deep features for prostate cancer grading on mpMRI.
Khanfari H; Mehranfar S; Cheki M; Mohammadi Sadr M; Moniri S; Heydarheydari S; Rezaeijo SM
BMC Med Imaging; 2023 Nov; 23(1):195. PubMed ID: 37993801
[TBL] [Abstract][Full Text] [Related]
12. The Effect of Image Resampling on the Performance of Radiomics-Based Artificial Intelligence in Multicenter Prostate MRI.
Bleker J; Roest C; Yakar D; Huisman H; Kwee TC
J Magn Reson Imaging; 2024 May; 59(5):1800-1806. PubMed ID: 37572098
[TBL] [Abstract][Full Text] [Related]
13. Advanced zoomed diffusion-weighted imaging vs. full-field-of-view diffusion-weighted imaging in prostate cancer detection: a radiomic features study.
Hu L; Zhou DW; Fu CX; Benkert T; Jiang CY; Li RT; Wei LM; Zhao JG
Eur Radiol; 2021 Mar; 31(3):1760-1769. PubMed ID: 32935192
[TBL] [Abstract][Full Text] [Related]
14. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
Wang X; Wan Q; Chen H; Li Y; Li X
Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
[TBL] [Abstract][Full Text] [Related]
15. Imaging biomarker analysis of advanced multiparametric MRI for glioma grading.
Vamvakas A; Williams SC; Theodorou K; Kapsalaki E; Fountas K; Kappas C; Vassiou K; Tsougos I
Phys Med; 2019 Apr; 60():188-198. PubMed ID: 30910431
[TBL] [Abstract][Full Text] [Related]
16. Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer.
Merisaari H; Taimen P; Shiradkar R; Ettala O; Pesola M; Saunavaara J; Boström PJ; Madabhushi A; Aronen HJ; Jambor I
Magn Reson Med; 2020 Jun; 83(6):2293-2309. PubMed ID: 31703155
[TBL] [Abstract][Full Text] [Related]
17. Multiparametric MRI in detection and staging of prostate cancer.
Boesen L
Dan Med J; 2017 Feb; 64(2):. PubMed ID: 28157066
[TBL] [Abstract][Full Text] [Related]
18. Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors.
Ginsburg SB; Viswanath SE; Bloch BN; Rofsky NM; Genega EM; Lenkinski RE; Madabhushi A
J Magn Reson Imaging; 2015 May; 41(5):1383-93. PubMed ID: 24943647
[TBL] [Abstract][Full Text] [Related]
19. Relaxation along fictitious field, diffusion-weighted imaging, and T2 mapping of prostate cancer: Prediction of cancer aggressiveness.
Jambor I; Pesola M; Merisaari H; Taimen P; Boström PJ; Liimatainen T; Aronen HJ
Magn Reson Med; 2016 May; 75(5):2130-40. PubMed ID: 26094849
[TBL] [Abstract][Full Text] [Related]
20. Prediction of prostate cancer aggressiveness using
Movahedi P; Merisaari H; Perez IM; Taimen P; Kemppainen J; Kuisma A; Eskola O; Teuho J; Saunavaara J; Pesola M; Kähkönen E; Ettala O; Liimatainen T; Pahikkala T; Boström P; Aronen H; Minn H; Jambor I
Sci Rep; 2020 Jun; 10(1):9407. PubMed ID: 32523075
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
