195 related articles for article (PubMed ID: 37871450)
1. Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images.
Bi L; Buehner U; Fu X; Williamson T; Choong P; Kim J
Comput Methods Programs Biomed; 2024 Jan; 243():107875. PubMed ID: 37871450
[TBL] [Abstract][Full Text] [Related]
2. Hyper-fusion network for semi-automatic segmentation of skin lesions.
Bi L; Fulham M; Kim J
Med Image Anal; 2022 Feb; 76():102334. PubMed ID: 34923251
[TBL] [Abstract][Full Text] [Related]
3. A new architecture combining convolutional and transformer-based networks for automatic 3D multi-organ segmentation on CT images.
Li C; Bagher-Ebadian H; Sultan R; Elshaikh M; Movsas B; Zhu D; Chetty IJ
Med Phys; 2023 Nov; 50(11):6990-7002. PubMed ID: 37738468
[TBL] [Abstract][Full Text] [Related]
4. Automatic segmentation and grading of ankylosing spondylitis on MR images via lightweight hybrid multi-scale convolutional neural network with reinforcement learning.
Gou S; Lu Y; Tong N; Huang L; Liu N; Han Q
Phys Med Biol; 2021 Oct; 66(20):. PubMed ID: 34517352
[No Abstract] [Full Text] [Related]
5. Dual encoder network with transformer-CNN for multi-organ segmentation.
Hong Z; Chen M; Hu W; Yan S; Qu A; Chen L; Chen J
Med Biol Eng Comput; 2023 Mar; 61(3):661-671. PubMed ID: 36580181
[TBL] [Abstract][Full Text] [Related]
6. Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-guided Semi-supervised Medical Image Segmentation.
Xiao Z; Su Y; Deng Z; Zhang W
Comput Methods Programs Biomed; 2022 Nov; 226():107099. PubMed ID: 36116398
[TBL] [Abstract][Full Text] [Related]
7. MS-TCNet: An effective Transformer-CNN combined network using multi-scale feature learning for 3D medical image segmentation.
Ao Y; Shi W; Ji B; Miao Y; He W; Jiang Z
Comput Biol Med; 2024 Mar; 170():108057. PubMed ID: 38301516
[TBL] [Abstract][Full Text] [Related]
8. Automatic liver segmentation by integrating fully convolutional networks into active contour models.
Guo X; Schwartz LH; Zhao B
Med Phys; 2019 Oct; 46(10):4455-4469. PubMed ID: 31356688
[TBL] [Abstract][Full Text] [Related]
9. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Cross-convolutional transformer for automated multi-organs segmentation in a variety of medical images.
Wang J; Zhao H; Liang W; Wang S; Zhang Y
Phys Med Biol; 2023 Jan; 68(3):. PubMed ID: 36623323
[No Abstract] [Full Text] [Related]
13. 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]
14. An iterative multi-path fully convolutional neural network for automatic cardiac segmentation in cine MR images.
Ma Z; Wu X; Wang X; Song Q; Yin Y; Cao K; Wang Y; Zhou J
Med Phys; 2019 Dec; 46(12):5652-5665. PubMed ID: 31605627
[TBL] [Abstract][Full Text] [Related]
15. A modality-collaborative convolution and transformer hybrid network for unpaired multi-modal medical image segmentation with limited annotations.
Liu H; Zhuang Y; Song E; Xu X; Ma G; Cetinkaya C; Hung CC
Med Phys; 2023 Sep; 50(9):5460-5478. PubMed ID: 36864700
[TBL] [Abstract][Full Text] [Related]
16. An efficient brain tumor image classifier by combining multi-pathway cascaded deep neural network and handcrafted features in MR images.
Bal A; Banerjee M; Chaki R; Sharma P
Med Biol Eng Comput; 2021 Aug; 59(7-8):1495-1527. PubMed ID: 34184181
[TBL] [Abstract][Full Text] [Related]
17. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
18. Brain tumor segmentation using holistically nested neural networks in MRI images.
Zhuge Y; Krauze AV; Ning H; Cheng JY; Arora BC; Camphausen K; Miller RW
Med Phys; 2017 Oct; 44(10):5234-5243. PubMed ID: 28736864
[TBL] [Abstract][Full Text] [Related]
19. A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance images.
Bevilacqua V; Brunetti A; Cascarano GD; Guerriero A; Pesce F; Moschetta M; Gesualdo L
BMC Med Inform Decis Mak; 2019 Dec; 19(Suppl 9):244. PubMed ID: 31830973
[TBL] [Abstract][Full Text] [Related]
20. Fully automated cardiac MRI segmentation using dilated residual network.
Ahmad F; Hou W; Xiong J; Xia Z
Med Phys; 2023 Apr; 50(4):2162-2175. PubMed ID: 36395472
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]