404 related articles for article (PubMed ID: 31630010)
1. Semi-supervised mp-MRI data synthesis with StitchLayer and auxiliary distance maximization.
Wang Z; Lin Y; Cheng KT; Yang X
Med Image Anal; 2020 Jan; 59():101565. PubMed ID: 31630010
[TBL] [Abstract][Full Text] [Related]
2. Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.
Yang X; Liu C; Wang Z; Yang J; Min HL; Wang L; Cheng KT
Med Image Anal; 2017 Dec; 42():212-227. PubMed ID: 28850876
[TBL] [Abstract][Full Text] [Related]
3. Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks.
Le MH; Chen J; Wang L; Wang Z; Liu W; Cheng KT; Yang X
Phys Med Biol; 2017 Jul; 62(16):6497-6514. PubMed ID: 28582269
[TBL] [Abstract][Full Text] [Related]
4. Bi-Modality Medical Image Synthesis Using Semi-Supervised Sequential Generative Adversarial Networks.
Yang X; Lin Y; Wang Z; Li X; Cheng KT
IEEE J Biomed Health Inform; 2020 Mar; 24(3):855-865. PubMed ID: 31217133
[TBL] [Abstract][Full Text] [Related]
5. Transition zone prostate cancer: Logistic regression and machine-learning models of quantitative ADC, shape and texture features are highly accurate for diagnosis.
Wu M; Krishna S; Thornhill RE; Flood TA; McInnes MDF; Schieda N
J Magn Reson Imaging; 2019 Sep; 50(3):940-950. PubMed ID: 30701625
[TBL] [Abstract][Full Text] [Related]
6. Fully automated detection of prostate transition zone tumors on T2-weighted and apparent diffusion coefficient (ADC) map MR images using U-Net ensemble.
Wong T; Schieda N; Sathiadoss P; Haroon M; Abreu-Gomez J; Ukwatta E
Med Phys; 2021 Nov; 48(11):6889-6900. PubMed ID: 34418108
[TBL] [Abstract][Full Text] [Related]
7. Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.
Wang Z; Liu C; Cheng D; Wang L; Yang X; Cheng KT
IEEE Trans Med Imaging; 2018 May; 37(5):1127-1139. PubMed ID: 29727276
[TBL] [Abstract][Full Text] [Related]
8. Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.
Aldoj N; Lukas S; Dewey M; Penzkofer T
Eur Radiol; 2020 Feb; 30(2):1243-1253. PubMed ID: 31468158
[TBL] [Abstract][Full Text] [Related]
9. Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks.
Lai CC; Wang HK; Wang FN; Peng YC; Lin TP; Peng HH; Shen SH
Sensors (Basel); 2021 Apr; 21(8):. PubMed ID: 33921451
[TBL] [Abstract][Full Text] [Related]
10. A deep dive into understanding tumor foci classification using multiparametric MRI based on convolutional neural network.
Zong W; Lee JK; Liu C; Carver EN; Feldman AM; Janic B; Elshaikh MA; Pantelic MV; Hearshen D; Chetty IJ; Movsas B; Wen N
Med Phys; 2020 Sep; 47(9):4077-4086. PubMed ID: 32449176
[TBL] [Abstract][Full Text] [Related]
11. Prostate Cancer Differentiation and Aggressiveness: Assessment With a Radiomic-Based Model vs. PI-RADS v2.
Chen T; Li M; Gu Y; Zhang Y; Yang S; Wei C; Wu J; Li X; Zhao W; Shen J
J Magn Reson Imaging; 2019 Mar; 49(3):875-884. PubMed ID: 30230108
[TBL] [Abstract][Full Text] [Related]
12. Automated segmentation of prostate zonal anatomy on T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U-Nets.
Zabihollahy F; Schieda N; Krishna Jeyaraj S; Ukwatta E
Med Phys; 2019 Jul; 46(7):3078-3090. PubMed ID: 31002381
[TBL] [Abstract][Full Text] [Related]
13. Retinal Image Synthesis and Semi-Supervised Learning for Glaucoma Assessment.
Diaz-Pinto A; Colomer A; Naranjo V; Morales S; Xu Y; Frangi AF
IEEE Trans Med Imaging; 2019 Sep; 38(9):2211-2218. PubMed ID: 30843823
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Prostate cancer classification with multiparametric MRI transfer learning model.
Yuan Y; Qin W; Buyyounouski M; Ibragimov B; Hancock S; Han B; Xing L
Med Phys; 2019 Feb; 46(2):756-765. PubMed ID: 30597561
[TBL] [Abstract][Full Text] [Related]
16. Lumbar Spine Computed Tomography to Magnetic Resonance Imaging Synthesis Using Generative Adversarial Network: Visual Turing Test.
Hong KT; Cho Y; Kang CH; Ahn KS; Lee H; Kim J; Hong SJ; Kim BH; Shim E
Diagnostics (Basel); 2022 Feb; 12(2):. PubMed ID: 35204619
[TBL] [Abstract][Full Text] [Related]
17. Generative Adversarial Network for Medical Images (MI-GAN).
Iqbal T; Ali H
J Med Syst; 2018 Oct; 42(11):231. PubMed ID: 30315368
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network.
Han L; Huang Y; Dou H; Wang S; Ahamad S; Luo H; Liu Q; Fan J; Zhang J
Comput Methods Programs Biomed; 2020 Jun; 189():105275. PubMed ID: 31978805
[TBL] [Abstract][Full Text] [Related]
20. Texture features on T2-weighted magnetic resonance imaging: new potential biomarkers for prostate cancer aggressiveness.
Vignati A; Mazzetti S; Giannini V; Russo F; Bollito E; Porpiglia F; Stasi M; Regge D
Phys Med Biol; 2015 Apr; 60(7):2685-701. PubMed ID: 25768265
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
