138 related articles for article (PubMed ID: 30387757)
1. Direct Segmentation-Based Full Quantification for Left Ventricle via Deep Multi-Task Regression Learning Network.
Du X; Tang R; Yin S; Zhang Y; Li S
IEEE J Biomed Health Inform; 2019 May; 23(3):942-948. PubMed ID: 30387757
[TBL] [Abstract][Full Text] [Related]
2. Automatic left ventricle segmentation from cardiac magnetic resonance images using a capsule network.
He Y; Qin W; Wu Y; Zhang M; Yang Y; Liu X; Zheng H; Liang D; Hu Z
J Xray Sci Technol; 2020; 28(3):541-553. PubMed ID: 32176675
[TBL] [Abstract][Full Text] [Related]
3. A deep learning-based approach for automatic segmentation and quantification of the left ventricle from cardiac cine MR images.
Abdeltawab H; Khalifa F; Taher F; Alghamdi NS; Ghazal M; Beache G; Mohamed T; Keynton R; El-Baz A
Comput Med Imaging Graph; 2020 Apr; 81():101717. PubMed ID: 32222684
[TBL] [Abstract][Full Text] [Related]
4. Fully automated segmentation of the left ventricle in cine cardiac MRI using neural network regression.
Tan LK; McLaughlin RA; Lim E; Abdul Aziz YF; Liew YM
J Magn Reson Imaging; 2018 Jul; 48(1):140-152. PubMed ID: 29316024
[TBL] [Abstract][Full Text] [Related]
5. Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.
Tan LK; Liew YM; Lim E; McLaughlin RA
Med Image Anal; 2017 Jul; 39():78-86. PubMed ID: 28437634
[TBL] [Abstract][Full Text] [Related]
6. Encoder-decoder with dense dilated spatial pyramid pooling for prostate MR images segmentation.
Geng L; Wang J; Xiao Z; Tong J; Zhang F; Wu J
Comput Assist Surg (Abingdon); 2019 Oct; 24(sup2):13-19. PubMed ID: 31424279
[TBL] [Abstract][Full Text] [Related]
7. DeepCQ: Deep multi-task conditional quantification network for estimation of left ventricle parameters.
Chen R; Xu C; Dong Z; Liu Y; Du X
Comput Methods Programs Biomed; 2020 Feb; 184():105288. PubMed ID: 31901611
[TBL] [Abstract][Full Text] [Related]
8. Full left ventricle quantification via deep multitask relationships learning.
Xue W; Brahm G; Pandey S; Leung S; Li S
Med Image Anal; 2018 Jan; 43():54-65. PubMed ID: 28987903
[TBL] [Abstract][Full Text] [Related]
9. Neural multi-atlas label fusion: Application to cardiac MR images.
Yang H; Sun J; Li H; Wang L; Xu Z
Med Image Anal; 2018 Oct; 49():60-75. PubMed ID: 30099151
[TBL] [Abstract][Full Text] [Related]
10. A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.
Avendi MR; Kheradvar A; Jafarkhani H
Med Image Anal; 2016 May; 30():108-119. PubMed ID: 26917105
[TBL] [Abstract][Full Text] [Related]
11. Commensal correlation network between segmentation and direct area estimation for bi-ventricle quantification.
Luo G; Dong S; Wang W; Wang K; Cao S; Tam C; Zhang H; Howey J; Ohorodnyk P; Li S
Med Image Anal; 2020 Jan; 59():101591. PubMed ID: 31704452
[TBL] [Abstract][Full Text] [Related]
12. Dilated-Inception Net: Multi-Scale Feature Aggregation for Cardiac Right Ventricle Segmentation.
Li J; Yu ZL; Gu Z; Liu H; Li Y
IEEE Trans Biomed Eng; 2019 Dec; 66(12):3499-3508. PubMed ID: 30932820
[TBL] [Abstract][Full Text] [Related]
13. Spatio-Temporal Multi-Task Learning for Cardiac MRI Left Ventricle Quantification.
Vesal S; Gu M; Maier A; Ravikumar N
IEEE J Biomed Health Inform; 2021 Jul; 25(7):2698-2709. PubMed ID: 33351771
[TBL] [Abstract][Full Text] [Related]
14. Multi-Views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images.
Luo G; Dong S; Wang K; Zuo W; Cao S; Zhang H
IEEE Trans Biomed Eng; 2018 Sep; 65(9):1924-1934. PubMed ID: 29035205
[TBL] [Abstract][Full Text] [Related]
15. Estimation of the Volume of the Left Ventricle From MRI Images Using Deep Neural Networks.
Liao F; Chen X; Hu X; Song S
IEEE Trans Cybern; 2019 Feb; 49(2):495-504. PubMed ID: 29990055
[TBL] [Abstract][Full Text] [Related]
16. Cardiac-DeepIED: Automatic Pixel-Level Deep Segmentation for Cardiac Bi-Ventricle Using Improved End-to-End Encoder-Decoder Network.
Du X; Yin S; Tang R; Zhang Y; Li S
IEEE J Transl Eng Health Med; 2019; 7():1900110. PubMed ID: 30949419
[TBL] [Abstract][Full Text] [Related]
17. Comparative analysis of U-Net and TLMDB GAN for the cardiovascular segmentation of the ventricles in the heart.
Zhang Y; Feng J; Guo X; Ren Y
Comput Methods Programs Biomed; 2022 Mar; 215():106614. PubMed ID: 35066315
[TBL] [Abstract][Full Text] [Related]
18. MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography.
Moradi S; Oghli MG; Alizadehasl A; Shiri I; Oveisi N; Oveisi M; Maleki M; Dhooge J
Phys Med; 2019 Nov; 67():58-69. PubMed ID: 31671333
[TBL] [Abstract][Full Text] [Related]
19. 3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.
Li X; Dou Q; Chen H; Fu CW; Qi X; Belavý DL; Armbrecht G; Felsenberg D; Zheng G; Heng PA
Med Image Anal; 2018 Apr; 45():41-54. PubMed ID: 29414435
[TBL] [Abstract][Full Text] [Related]
20. Segmentation of histological images and fibrosis identification with a convolutional neural network.
Fu X; Liu T; Xiong Z; Smaill BH; Stiles MK; Zhao J
Comput Biol Med; 2018 Jul; 98():147-158. PubMed ID: 29793096
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]