1018 related articles for article (PubMed ID: 32143788)
1. Multi-planar 3D breast segmentation in MRI via deep convolutional neural networks.
Piantadosi G; Sansone M; Fusco R; Sansone C
Artif Intell Med; 2020 Mar; 103():101781. PubMed ID: 32143788
[TBL] [Abstract][Full Text] [Related]
2. Visual ensemble selection of deep convolutional neural networks for 3D segmentation of breast tumors on dynamic contrast enhanced MRI.
Rahimpour M; Saint Martin MJ; Frouin F; Akl P; Orlhac F; Koole M; Malhaire C
Eur Radiol; 2023 Feb; 33(2):959-969. PubMed ID: 36074262
[TBL] [Abstract][Full Text] [Related]
3. Fast and Precise Hippocampus Segmentation Through Deep Convolutional Neural Network Ensembles and Transfer Learning.
Ataloglou D; Dimou A; Zarpalas D; Daras P
Neuroinformatics; 2019 Oct; 17(4):563-582. PubMed ID: 30877605
[TBL] [Abstract][Full Text] [Related]
4. Deep Convolutional Neural Networks-Based Automatic Breast Segmentation and Mass Detection in DCE-MRI.
Jiao H; Jiang X; Pang Z; Lin X; Huang Y; Li L
Comput Math Methods Med; 2020; 2020():2413706. PubMed ID: 32454879
[TBL] [Abstract][Full Text] [Related]
5. Task-based assessment of a convolutional neural network for segmenting breast lesions for radiomic analysis.
Spuhler KD; Ding J; Liu C; Sun J; Serrano-Sosa M; Moriarty M; Huang C
Magn Reson Med; 2019 Aug; 82(2):786-795. PubMed ID: 30957936
[TBL] [Abstract][Full Text] [Related]
6. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
Burton W; Myers C; Rullkoetter P
Comput Methods Programs Biomed; 2020 Jun; 189():105328. PubMed ID: 31958580
[TBL] [Abstract][Full Text] [Related]
7. 3D Breast Cancer Segmentation in DCE-MRI Using Deep Learning With Weak Annotation.
Park GE; Kim SH; Nam Y; Kang J; Park M; Kang BJ
J Magn Reson Imaging; 2024 Jun; 59(6):2252-2262. PubMed ID: 37596823
[TBL] [Abstract][Full Text] [Related]
8. An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.
Fashandi H; Kuling G; Lu Y; Wu H; Martel AL
Med Phys; 2019 Mar; 46(3):1230-1244. PubMed ID: 30609062
[TBL] [Abstract][Full Text] [Related]
9. Improvement of semantic segmentation through transfer learning of multi-class regions with convolutional neural networks on supine and prone breast MRI images.
Ham S; Kim M; Lee S; Wang CB; Ko B; Kim N
Sci Rep; 2023 Apr; 13(1):6877. PubMed ID: 37106024
[TBL] [Abstract][Full Text] [Related]
10. Automated fibroglandular tissue segmentation in breast MRI using generative adversarial networks.
Ma X; Wang J; Zheng X; Liu Z; Long W; Zhang Y; Wei J; Lu Y
Phys Med Biol; 2020 May; 65(10):105006. PubMed ID: 32155611
[TBL] [Abstract][Full Text] [Related]
11. Using deep learning to segment breast and fibroglandular tissue in MRI volumes.
Dalmış MU; Litjens G; Holland K; Setio A; Mann R; Karssemeijer N; Gubern-Mérida A
Med Phys; 2017 Feb; 44(2):533-546. PubMed ID: 28035663
[TBL] [Abstract][Full Text] [Related]
12. Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.
Naceur MB; Saouli R; Akil M; Kachouri R
Comput Methods Programs Biomed; 2018 Nov; 166():39-49. PubMed ID: 30415717
[TBL] [Abstract][Full Text] [Related]
13. New one-step model of breast tumor locating based on deep learning.
Tao C; Chen K; Han L; Peng Y; Li C; Hua Z; Lin J
J Xray Sci Technol; 2019; 27(5):839-856. PubMed ID: 31306148
[TBL] [Abstract][Full Text] [Related]
14. Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.
Lavdas I; Glocker B; Kamnitsas K; Rueckert D; Mair H; Sandhu A; Taylor SA; Aboagye EO; Rockall AG
Med Phys; 2017 Oct; 44(10):5210-5220. PubMed ID: 28756622
[TBL] [Abstract][Full Text] [Related]
15. Lesion detection in women breast's dynamic contrast-enhanced magnetic resonance imaging using deep learning.
Saikia S; Si T; Deb D; Bora K; Mallik S; Maulik U; Zhao Z
Sci Rep; 2023 Dec; 13(1):22555. PubMed ID: 38110462
[TBL] [Abstract][Full Text] [Related]
16. Deep morphology aided diagnosis network for segmentation of carotid artery vessel wall and diagnosis of carotid atherosclerosis on black-blood vessel wall MRI.
Wu J; Xin J; Yang X; Sun J; Xu D; Zheng N; Yuan C
Med Phys; 2019 Dec; 46(12):5544-5561. PubMed ID: 31356693
[TBL] [Abstract][Full Text] [Related]
17. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.
Gros C; De Leener B; Badji A; Maranzano J; Eden D; Dupont SM; Talbott J; Zhuoquiong R; Liu Y; Granberg T; Ouellette R; Tachibana Y; Hori M; Kamiya K; Chougar L; Stawiarz L; Hillert J; Bannier E; Kerbrat A; Edan G; Labauge P; Callot V; Pelletier J; Audoin B; Rasoanandrianina H; Brisset JC; Valsasina P; Rocca MA; Filippi M; Bakshi R; Tauhid S; Prados F; Yiannakas M; Kearney H; Ciccarelli O; Smith S; Treaba CA; Mainero C; Lefeuvre J; Reich DS; Nair G; Auclair V; McLaren DG; Martin AR; Fehlings MG; Vahdat S; Khatibi A; Doyon J; Shepherd T; Charlson E; Narayanan S; Cohen-Adad J
Neuroimage; 2019 Jan; 184():901-915. PubMed ID: 30300751
[TBL] [Abstract][Full Text] [Related]
18. DENSE-INception U-net for medical image segmentation.
Zhang Z; Wu C; Coleman S; Kerr D
Comput Methods Programs Biomed; 2020 Aug; 192():105395. PubMed ID: 32163817
[TBL] [Abstract][Full Text] [Related]
19. Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net.
Zhang Y; Chen JH; Chang KT; Park VY; Kim MJ; Chan S; Chang P; Chow D; Luk A; Kwong T; Su MY
Acad Radiol; 2019 Nov; 26(11):1526-1535. PubMed ID: 30713130
[TBL] [Abstract][Full Text] [Related]
20. Weakly supervised 3D deep learning for breast cancer classification and localization of the lesions in MR images.
Zhou J; Luo LY; Dou Q; Chen H; Chen C; Li GJ; Jiang ZF; Heng PA
J Magn Reson Imaging; 2019 Oct; 50(4):1144-1151. PubMed ID: 30924997
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
