531 related articles for article (PubMed ID: 34796528)
1. Progressive attention module for segmentation of volumetric medical images.
Zhang M; Pan H; Zhu Y; Gu Y
Med Phys; 2022 Jan; 49(1):295-308. PubMed ID: 34796528
[TBL] [Abstract][Full Text] [Related]
2. Evaluation of multislice inputs to convolutional neural networks for medical image segmentation.
Vu MH; Grimbergen G; Nyholm T; Löfstedt T
Med Phys; 2020 Dec; 47(12):6216-6231. PubMed ID: 33169365
[TBL] [Abstract][Full Text] [Related]
3. Improved UNet with Attention for Medical Image Segmentation.
Al Qurri A; Almekkawy M
Sensors (Basel); 2023 Oct; 23(20):. PubMed ID: 37896682
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. PA-ResSeg: A phase attention residual network for liver tumor segmentation from multiphase CT images.
Xu Y; Cai M; Lin L; Zhang Y; Hu H; Peng Z; Zhang Q; Chen Q; Mao X; Iwamoto Y; Han XH; Chen YW; Tong R
Med Phys; 2021 Jul; 48(7):3752-3766. PubMed ID: 33950526
[TBL] [Abstract][Full Text] [Related]
6. Tumor attention networks: Better feature selection, better tumor segmentation.
Pang S; Du A; Orgun MA; Wang Y; Yu Z
Neural Netw; 2021 Aug; 140():203-222. PubMed ID: 33780873
[TBL] [Abstract][Full Text] [Related]
7. CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation.
Gu R; Wang G; Song T; Huang R; Aertsen M; Deprest J; Ourselin S; Vercauteren T; Zhang S
IEEE Trans Med Imaging; 2021 Feb; 40(2):699-711. PubMed ID: 33136540
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. MESTrans: Multi-scale embedding spatial transformer for medical image segmentation.
Liu Y; Zhu Y; Xin Y; Zhang Y; Yang D; Xu T
Comput Methods Programs Biomed; 2023 May; 233():107493. PubMed ID: 36965298
[TBL] [Abstract][Full Text] [Related]
10. Swin Unet3D: a three-dimensional medical image segmentation network combining vision transformer and convolution.
Cai Y; Long Y; Han Z; Liu M; Zheng Y; Yang W; Chen L
BMC Med Inform Decis Mak; 2023 Feb; 23(1):33. PubMed ID: 36788560
[TBL] [Abstract][Full Text] [Related]
11. Fusing 2D and 3D convolutional neural networks for the segmentation of aorta and coronary arteries from CT images.
Gu L; Cai XC
Artif Intell Med; 2021 Nov; 121():102189. PubMed ID: 34763804
[TBL] [Abstract][Full Text] [Related]
12. Automatic segmentation of tumors and affected organs in the abdomen using a 3D hybrid model for computed tomography imaging.
Qayyum A; Lalande A; Meriaudeau F
Comput Biol Med; 2020 Dec; 127():104097. PubMed ID: 33142142
[TBL] [Abstract][Full Text] [Related]
13. CeLNet: a correlation-enhanced lightweight network for medical image segmentation.
Zhang B; Wang X; Liu L; Zhang D; Huang X; Xia M; Jiang W; Huang X
Phys Med Biol; 2023 May; 68(11):. PubMed ID: 37172613
[No Abstract] [Full Text] [Related]
14. Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.
Farhangi MM; Petrick N; Sahiner B; Frigui H; Amini AA; Pezeshk A
Med Phys; 2020 Jun; 47(5):2150-2160. PubMed ID: 32030769
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. HFCF-Net: A hybrid-feature cross fusion network for COVID-19 lesion segmentation from CT volumetric images.
Wang Y; Yang Q; Tian L; Zhou X; Rekik I; Huang H
Med Phys; 2022 Jun; 49(6):3797-3815. PubMed ID: 35301729
[TBL] [Abstract][Full Text] [Related]
17. An Efficient and Accurate 3D Multiple-Contextual Semantic Segmentation Network for Medical Volumetric Images.
Li H; Iwamoto Y; Han X; Furukawa A; Kanasaki S; Chen YW
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3309-3312. PubMed ID: 34891948
[TBL] [Abstract][Full Text] [Related]
18. Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.
Dong X; Xu S; Liu Y; Wang A; Saripan MI; Li L; Zhang X; Lu L
Cancer Imaging; 2020 Aug; 20(1):53. PubMed ID: 32738913
[TBL] [Abstract][Full Text] [Related]
19. Automated multi-modal Transformer network (AMTNet) for 3D medical images segmentation.
Zheng S; Tan J; Jiang C; Li L
Phys Med Biol; 2023 Jan; 68(2):. PubMed ID: 36595252
[No Abstract] [Full Text] [Related]
20. HFRU-Net: High-Level Feature Fusion and Recalibration UNet for Automatic Liver and Tumor Segmentation in CT Images.
Kushnure DT; Talbar SN
Comput Methods Programs Biomed; 2022 Jan; 213():106501. PubMed ID: 34752959
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]