135 related articles for article (PubMed ID: 36798450)
1. Automatic Segmentation of Uterine Cavity and Placenta on MR Images Using Deep Learning.
Shahedi M; Dormer JD; Do QN; Xi Y; Lewis MA; Herrera CL; Spong CY; Madhuranthakam AJ; Twickler DM; Fei B
Proc SPIE Int Soc Opt Eng; 2022; 12036():. PubMed ID: 36798450
[TBL] [Abstract][Full Text] [Related]
2. Segmentation of uterus and placenta in MR images using a fully convolutional neural network.
Shahedi M; Dormer JD; T T AD; Do QN; Xi Y; Lewis MA; Madhuranthakam AJ; Twickler DM; Fei B
Proc SPIE Int Soc Opt Eng; 2020 Feb; 11314():. PubMed ID: 32476702
[TBL] [Abstract][Full Text] [Related]
3. Deep learning based automatic segmentation of the placenta and uterine cavity on prenatal MR images.
Huang J; Do QN; Shahed M; Xi Y; Lewis MA; Herrera CL; Owen D; Spong CY; Madhuranthakam AJ; Twickler DM; Fei B
Proc SPIE Int Soc Opt Eng; 2023 Feb; 12465():. PubMed ID: 38486806
[TBL] [Abstract][Full Text] [Related]
4. Deep learning-based segmentation of the placenta and uterus on MR images.
Shahedi M; Spong CY; Dormer JD; Do QN; Xi Y; Lewis MA; Herrera C; Madhuranthakam AJ; Twickler DM; Fei B
J Med Imaging (Bellingham); 2021 Sep; 8(5):054001. PubMed ID: 34589556
[No Abstract] [Full Text] [Related]
5. Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI.
Liu Y; Zabihollahy F; Yan R; Lee B; Janzen C; Devaskar SU; Sung K
J Magn Reson Imaging; 2023 May; 57(5):1533-1540. PubMed ID: 37021577
[TBL] [Abstract][Full Text] [Related]
6. An Adapted Deep Convolutional Neural Network for Automatic Measurement of Pancreatic Fat and Pancreatic Volume in Clinical Multi-Protocol Magnetic Resonance Images: A Retrospective Study with Multi-Ethnic External Validation.
Yang JZ; Zhao J; Nemati R; Yin X; He KH; Plank L; Murphy R; Lu J
Biomedicines; 2022 Nov; 10(11):. PubMed ID: 36428558
[TBL] [Abstract][Full Text] [Related]
7. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
Kawula M; Hadi I; Nierer L; Vagni M; Cusumano D; Boldrini L; Placidi L; Corradini S; Belka C; Landry G; Kurz C
Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
[TBL] [Abstract][Full Text] [Related]
8. Fully automated multiorgan segmentation of female pelvic magnetic resonance images with coarse-to-fine convolutional neural network.
Zabihollahy F; Viswanathan AN; Schmidt EJ; Morcos M; Lee J
Med Phys; 2021 Nov; 48(11):7028-7042. PubMed ID: 34609756
[TBL] [Abstract][Full Text] [Related]
9. Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.
Lin YC; Lin CH; Lu HY; Chiang HJ; Wang HK; Huang YT; Ng SH; Hong JH; Yen TC; Lai CH; Lin G
Eur Radiol; 2020 Mar; 30(3):1297-1305. PubMed ID: 31712961
[TBL] [Abstract][Full Text] [Related]
10. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
Tong N; Gou S; Yang S; Cao M; Sheng K
Med Phys; 2019 Jun; 46(6):2669-2682. PubMed ID: 31002188
[TBL] [Abstract][Full Text] [Related]
11. Automatic segmentation of the uterus on MRI using a convolutional neural network.
Kurata Y; Nishio M; Kido A; Fujimoto K; Yakami M; Isoda H; Togashi K
Comput Biol Med; 2019 Nov; 114():103438. PubMed ID: 31521902
[TBL] [Abstract][Full Text] [Related]
12. Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.
Laukamp KR; Pennig L; Thiele F; Reimer R; Görtz L; Shakirin G; Zopfs D; Timmer M; Perkuhn M; Borggrefe J
Clin Neuroradiol; 2021 Jun; 31(2):357-366. PubMed ID: 32060575
[TBL] [Abstract][Full Text] [Related]
13. Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT.
Bruns S; Wolterink JM; Takx RAP; van Hamersvelt RW; Suchá D; Viergever MA; Leiner T; Išgum I
Med Phys; 2020 Oct; 47(10):5048-5060. PubMed ID: 32786071
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.
Khalili N; Lessmann N; Turk E; Claessens N; Heus R; Kolk T; Viergever MA; Benders MJNL; Išgum I
Magn Reson Imaging; 2019 Dec; 64():77-89. PubMed ID: 31181246
[TBL] [Abstract][Full Text] [Related]
16. Convolutional neural network-based pelvic floor structure segmentation using magnetic resonance imaging in pelvic organ prolapse.
Feng F; Ashton-Miller JA; DeLancey JOL; Luo J
Med Phys; 2020 Sep; 47(9):4281-4293. PubMed ID: 32638370
[TBL] [Abstract][Full Text] [Related]
17. Automatic placental and fetal volume estimation by a convolutional neural network.
Kulseng CPS; Hillestad V; Eskild A; Gjesdal KI
Placenta; 2023 Mar; 134():23-29. PubMed ID: 36863128
[TBL] [Abstract][Full Text] [Related]
18. A distance map regularized CNN for cardiac cine MR image segmentation.
Dangi S; Linte CA; Yaniv Z
Med Phys; 2019 Dec; 46(12):5637-5651. PubMed ID: 31598971
[TBL] [Abstract][Full Text] [Related]
19. Fully automated multiorgan segmentation in abdominal magnetic resonance imaging with deep neural networks.
Chen Y; Ruan D; Xiao J; Wang L; Sun B; Saouaf R; Yang W; Li D; Fan Z
Med Phys; 2020 Oct; 47(10):4971-4982. PubMed ID: 32748401
[TBL] [Abstract][Full Text] [Related]
20. Automatic segmentation of high-risk clinical target volume for tandem-and-ovoids brachytherapy patients using an asymmetric dual-path convolutional neural network.
Cao Y; Vassantachart A; Ragab O; Bian S; Mitra P; Xu Z; Gallogly AZ; Cui J; Shen ZL; Balik S; Gribble M; Chang EL; Fan Z; Yang W
Med Phys; 2022 Mar; 49(3):1712-1722. PubMed ID: 35080018
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
