797 related articles for article (PubMed ID: 33212541)
1. Comparison of Prostate MRI Lesion Segmentation Agreement Between Multiple Radiologists and a Fully Automatic Deep Learning System.
Schelb P; Tavakoli AA; Tubtawee T; Hielscher T; Radtke JP; Görtz M; Schütz V; Kuder TA; Schimmöller L; Stenzinger A; Hohenfellner M; Schlemmer HP; Bonekamp D
Rofo; 2021 May; 193(5):559-573. PubMed ID: 33212541
[TBL] [Abstract][Full Text] [Related]
2. A Cascaded Deep Learning-Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging.
Mehralivand S; Yang D; Harmon SA; Xu D; Xu Z; Roth H; Masoudi S; Sanford TH; Kesani D; Lay NS; Merino MJ; Wood BJ; Pinto PA; Choyke PL; Turkbey B
Acad Radiol; 2022 Aug; 29(8):1159-1168. PubMed ID: 34598869
[TBL] [Abstract][Full Text] [Related]
3. Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.
Schelb P; Kohl S; Radtke JP; Wiesenfarth M; Kickingereder P; Bickelhaupt S; Kuder TA; Stenzinger A; Hohenfellner M; Schlemmer HP; Maier-Hein KH; Bonekamp D
Radiology; 2019 Dec; 293(3):607-617. PubMed ID: 31592731
[TBL] [Abstract][Full Text] [Related]
4. Application of a validated prostate MRI deep learning system to independent same-vendor multi-institutional data: demonstration of transferability.
Netzer N; Eith C; Bethge O; Hielscher T; Schwab C; Stenzinger A; Gnirs R; Schlemmer HP; Maier-Hein KH; Schimmöller L; Bonekamp D
Eur Radiol; 2023 Nov; 33(11):7463-7476. PubMed ID: 37507610
[TBL] [Abstract][Full Text] [Related]
5. A 3D-2D Hybrid U-Net Convolutional Neural Network Approach to Prostate Organ Segmentation of Multiparametric MRI.
Ushinsky A; Bardis M; Glavis-Bloom J; Uchio E; Chantaduly C; Nguyentat M; Chow D; Chang PD; Houshyar R
AJR Am J Roentgenol; 2021 Jan; 216(1):111-116. PubMed ID: 32812797
[TBL] [Abstract][Full Text] [Related]
6. Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy.
Soerensen SJC; Fan RE; Seetharaman A; Chen L; Shao W; Bhattacharya I; Kim YH; Sood R; Borre M; Chung BI; To'o KJ; Rusu M; Sonn GA
J Urol; 2021 Sep; 206(3):604-612. PubMed ID: 33878887
[TBL] [Abstract][Full Text] [Related]
7. Manual prostate cancer segmentation in MRI: interreader agreement and volumetric correlation with transperineal template core needle biopsy.
Liechti MR; Muehlematter UJ; Schneider AF; Eberli D; Rupp NJ; Hötker AM; Donati OF; Becker AS
Eur Radiol; 2020 Sep; 30(9):4806-4815. PubMed ID: 32306078
[TBL] [Abstract][Full Text] [Related]
8. Index lesion contouring on prostate MRI for targeted MRI/US fusion biopsy - Evaluation of mismatch between radiologists and urologists.
Ghafoor S; Steinebrunner F; Stocker D; Hötker AM; Schmid FA; Eberli D; Donati OF
Eur J Radiol; 2023 May; 162():110763. PubMed ID: 36898172
[TBL] [Abstract][Full Text] [Related]
9. Fully Automatic Deep Learning in Bi-institutional Prostate Magnetic Resonance Imaging: Effects of Cohort Size and Heterogeneity.
Netzer N; Weißer C; Schelb P; Wang X; Qin X; Görtz M; Schütz V; Radtke JP; Hielscher T; Schwab C; Stenzinger A; Kuder TA; Gnirs R; Hohenfellner M; Schlemmer HP; Maier-Hein KH; Bonekamp D
Invest Radiol; 2021 Dec; 56(12):799-808. PubMed ID: 34049336
[TBL] [Abstract][Full Text] [Related]
10. Development and validation of a deep learning model for breast lesion segmentation and characterization in multiparametric MRI.
Zhu J; Geng J; Shan W; Zhang B; Shen H; Dong X; Liu M; Li X; Cheng L
Front Oncol; 2022; 12():946580. PubMed ID: 36033449
[TBL] [Abstract][Full Text] [Related]
11. Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment.
Schelb P; Wang X; Radtke JP; Wiesenfarth M; Kickingereder P; Stenzinger A; Hohenfellner M; Schlemmer HP; Maier-Hein KH; Bonekamp D
Eur Radiol; 2021 Jan; 31(1):302-313. PubMed ID: 32767102
[TBL] [Abstract][Full Text] [Related]
12. Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.
Chen Y; Xing L; Yu L; Bagshaw HP; Buyyounouski MK; Han B
Med Phys; 2020 Dec; 47(12):6421-6429. PubMed ID: 33012016
[TBL] [Abstract][Full Text] [Related]
13. The effect of deep learning-based lesion segmentation on failure load calculations of metastatic femurs using finite element analysis.
Ataei A; Eggermont F; Verdonschot N; Lessmann N; Tanck E
Bone; 2024 Feb; 179():116987. PubMed ID: 38061504
[TBL] [Abstract][Full Text] [Related]
14. Fully automatic segmentation on prostate MR images based on cascaded fully convolution network.
Zhu Y; Wei R; Gao G; Ding L; Zhang X; Wang X; Zhang J
J Magn Reson Imaging; 2019 Apr; 49(4):1149-1156. PubMed ID: 30350434
[TBL] [Abstract][Full Text] [Related]
15. Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.
Korte JC; Hardcastle N; Ng SP; Clark B; Kron T; Jackson P
Med Phys; 2021 Dec; 48(12):7757-7772. PubMed ID: 34676555
[TBL] [Abstract][Full Text] [Related]
16. Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter Study.
Wennmann M; Neher P; Stanczyk N; Kahl KC; Kächele J; Weru V; Hielscher T; Grözinger M; Chmelik J; Zhang KS; Bauer F; Nonnenmacher T; Debic M; Sauer S; Rotkopf LT; Jauch A; Schlamp K; Mai EK; Weinhold N; Afat S; Horger M; Goldschmidt H; Schlemmer HP; Weber TF; Delorme S; Kurz FT; Maier-Hein K
Invest Radiol; 2023 Apr; 58(4):273-282. PubMed ID: 36256790
[TBL] [Abstract][Full Text] [Related]
17. Deep Learning for Real-time, Automatic, and Scanner-adapted Prostate (Zone) Segmentation of Transrectal Ultrasound, for Example, Magnetic Resonance Imaging-transrectal Ultrasound Fusion Prostate Biopsy.
van Sloun RJG; Wildeboer RR; Mannaerts CK; Postema AW; Gayet M; Beerlage HP; Salomon G; Wijkstra H; Mischi M
Eur Urol Focus; 2021 Jan; 7(1):78-85. PubMed ID: 31028016
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning Network for Segmentation of the Prostate Gland With Median Lobe Enlargement in T2-weighted MR Images: Comparison With Manual Segmentation Method.
Salvaggio G; Comelli A; Portoghese M; Cutaia G; Cannella R; Vernuccio F; Stefano A; Dispensa N; La Tona G; Salvaggio L; Calamia M; Gagliardo C; Lagalla R; Midiri M
Curr Probl Diagn Radiol; 2022; 51(3):328-333. PubMed ID: 34315623
[TBL] [Abstract][Full Text] [Related]
19. Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.
Zhang L; Mohamed AA; Chai R; Guo Y; Zheng B; Wu S
J Magn Reson Imaging; 2020 Feb; 51(2):635-643. PubMed ID: 31301201
[TBL] [Abstract][Full Text] [Related]
20. Fully Automatic Assessment of Background Parenchymal Enhancement on Breast MRI Using Machine-Learning Models.
Nam Y; Park GE; Kang J; Kim SH
J Magn Reson Imaging; 2021 Mar; 53(3):818-826. PubMed ID: 33219624
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]