107 related articles for article (PubMed ID: 36410304)
1. Temperature guided network for 3D joint segmentation of the pancreas and tumors.
Li Q; Liu X; He Y; Li D; Xue J
Neural Netw; 2023 Jan; 157():387-403. PubMed ID: 36410304
[TBL] [Abstract][Full Text] [Related]
2. Graph-enhanced U-Net for semi-supervised segmentation of pancreas from abdomen CT scan.
Liu S; Liang S; Huang X; Yuan X; Zhong T; Zhang Y
Phys Med Biol; 2022 Jul; 67(15):. PubMed ID: 35892477
[No Abstract] [Full Text] [Related]
3. Multiscale unsupervised domain adaptation for automatic pancreas segmentation in CT volumes using adversarial learning.
Zhu Y; Hu P; Li X; Tian Y; Bai X; Liang T; Li J
Med Phys; 2022 Sep; 49(9):5799-5818. PubMed ID: 35833617
[TBL] [Abstract][Full Text] [Related]
4. Inter-Slice Context Residual Learning for 3D Medical Image Segmentation.
Zhang J; Xie Y; Wang Y; Xia Y
IEEE Trans Med Imaging; 2021 Feb; 40(2):661-672. PubMed ID: 33125324
[TBL] [Abstract][Full Text] [Related]
5. Cascaded MultiTask 3-D Fully Convolutional Networks for Pancreas Segmentation.
Xue J; He K; Nie D; Adeli E; Shi Z; Lee SW; Zheng Y; Liu X; Li D; Shen D
IEEE Trans Cybern; 2021 Apr; 51(4):2153-2165. PubMed ID: 31869812
[TBL] [Abstract][Full Text] [Related]
6. Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.
Fu M; Wu W; Hong X; Liu Q; Jiang J; Ou Y; Zhao Y; Gong X
BMC Syst Biol; 2018 Apr; 12(Suppl 4):56. PubMed ID: 29745840
[TBL] [Abstract][Full Text] [Related]
7. Semi-supervised interactive fusion network for MR image segmentation.
Xu W; Bian Y; Lu Y; Meng Q; Zhu W; Shi F; Chen X; Shao C; Xiang D
Med Phys; 2023 Mar; 50(3):1586-1600. PubMed ID: 36345139
[TBL] [Abstract][Full Text] [Related]
8. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.
Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH
Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105
[TBL] [Abstract][Full Text] [Related]
9. Bounding box-based 3D AI model for user-guided volumetric segmentation of pancreatic ductal adenocarcinoma on standard-of-care CTs.
Mukherjee S; Korfiatis P; Khasawneh H; Rajamohan N; Patra A; Suman G; Singh A; Thakkar J; Patnam NG; Trivedi KH; Karbhari A; Chari ST; Truty MJ; Halfdanarson TR; Bolan CW; Sandrasegaran K; Majumder S; Goenka AH
Pancreatology; 2023 Aug; 23(5):522-529. PubMed ID: 37296006
[TBL] [Abstract][Full Text] [Related]
10. Deep pancreas segmentation with uncertain regions of shadowed sets.
Zheng H; Chen Y; Yue X; Ma C; Liu X; Yang P; Lu J
Magn Reson Imaging; 2020 May; 68():45-52. PubMed ID: 31987903
[TBL] [Abstract][Full Text] [Related]
11. Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.
Roth HR; Lu L; Lay N; Harrison AP; Farag A; Sohn A; Summers RM
Med Image Anal; 2018 Apr; 45():94-107. PubMed ID: 29427897
[TBL] [Abstract][Full Text] [Related]
12. Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation.
Zheng H; Qian L; Qin Y; Gu Y; Yang J
Med Phys; 2020 Nov; 47(11):5543-5554. PubMed ID: 32502278
[TBL] [Abstract][Full Text] [Related]
13. A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set.
Zhang Y; Wu J; Liu Y; Chen Y; Chen W; Wu EX; Li C; Tang X
Med Image Anal; 2021 Feb; 68():101884. PubMed ID: 33246228
[TBL] [Abstract][Full Text] [Related]
14. Automated pancreas segmentation and volumetry using deep neural network on computed tomography.
Lim SH; Kim YJ; Park YH; Kim D; Kim KG; Lee DH
Sci Rep; 2022 Mar; 12(1):4075. PubMed ID: 35260710
[TBL] [Abstract][Full Text] [Related]
15. 3D IFPN: Improved Feature Pyramid Network for Automatic Segmentation of Gastric Tumor.
Li H; Liu B; Zhang Y; Fu C; Han X; Du L; Gao W; Chen Y; Liu X; Wang Y; Wang T; Ma G; Lei B
Front Oncol; 2021; 11():618496. PubMed ID: 34094903
[TBL] [Abstract][Full Text] [Related]
16. Segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and texture descriptors.
Mahmoudi T; Kouzahkanan ZM; Radmard AR; Kafieh R; Salehnia A; Davarpanah AH; Arabalibeik H; Ahmadian A
Sci Rep; 2022 Feb; 12(1):3092. PubMed ID: 35197542
[TBL] [Abstract][Full Text] [Related]
17. 3D Dense Volumetric Network for Accurate Automated Pancreas Segmentation.
Wang R; Liu X; Shao H; Li Q; Zhong D
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3553-3556. PubMed ID: 34892006
[TBL] [Abstract][Full Text] [Related]
18. A Semiautomated Deep Learning Approach for Pancreas Segmentation.
Huang M; Huang C; Yuan J; Kong D
J Healthc Eng; 2021; 2021():3284493. PubMed ID: 34306587
[TBL] [Abstract][Full Text] [Related]
19. Pancreas segmentation based on an adversarial model under two-tier constraints.
Li M; Lian F; Guo S
Phys Med Biol; 2020 Nov; 65(22):225021. PubMed ID: 32906095
[TBL] [Abstract][Full Text] [Related]
20. Deep causal learning for pancreatic cancer segmentation in CT sequences.
Li C; Mao Y; Liang S; Li J; Wang Y; Guo Y
Neural Netw; 2024 Jul; 175():106294. PubMed ID: 38657562
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
