127 related articles for article (PubMed ID: 38657628)
1. GMAlignNet: multi-scale lightweight brain tumor image segmentation with enhanced semantic information consistency.
Song J; Lu X; Gu Y
Phys Med Biol; 2024 May; 69(11):. PubMed ID: 38657628
[TBL] [Abstract][Full Text] [Related]
2. [Fully Automatic Glioma Segmentation Algorithm of Magnetic Resonance Imaging Based on 3D-UNet With More Global Contextual Feature Extraction: An Improvement on Insufficient Extraction of Global Features].
Tian H; Wang Y; Ji Y; Rahman MM
Sichuan Da Xue Xue Bao Yi Xue Ban; 2024 Mar; 55(2):447-454. PubMed ID: 38645864
[TBL] [Abstract][Full Text] [Related]
3. SDS-Net: A lightweight 3D convolutional neural network with multi-branch attention for multimodal brain tumor accurate segmentation.
Wu Q; Pei Y; Cheng Z; Hu X; Wang C
Math Biosci Eng; 2023 Sep; 20(9):17384-17406. PubMed ID: 37920059
[TBL] [Abstract][Full Text] [Related]
4. A lightweight hierarchical convolution network for brain tumor segmentation.
Wang Y; Cao Y; Li J; Wu H; Wang S; Dong X; Yu H
BMC Bioinformatics; 2022 Dec; 22(Suppl 5):636. PubMed ID: 36513986
[TBL] [Abstract][Full Text] [Related]
5. Brain tumor magnetic resonance image segmentation by a multiscale contextual attention module combined with a deep residual UNet (MCA-ResUNet).
Cao T; Wang G; Ren L; Li Y; Wang H
Phys Med Biol; 2022 Apr; 67(9):. PubMed ID: 35294935
[No Abstract] [Full Text] [Related]
6. MSFR-Net: Multi-modality and single-modality feature recalibration network for brain tumor segmentation.
Li X; Jiang Y; Li M; Zhang J; Yin S; Luo H
Med Phys; 2023 Apr; 50(4):2249-2262. PubMed ID: 35962724
[TBL] [Abstract][Full Text] [Related]
7. A deep convolutional neural network for the automatic segmentation of glioblastoma brain tumor: Joint spatial pyramid module and attention mechanism network.
Liu H; Huang J; Li Q; Guan X; Tseng M
Artif Intell Med; 2024 Feb; 148():102776. PubMed ID: 38325925
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Scalable Swin Transformer network for brain tumor segmentation from incomplete MRI modalities.
Zhang D; Wang C; Chen T; Chen W; Shen Y
Artif Intell Med; 2024 Mar; 149():102788. PubMed ID: 38462288
[TBL] [Abstract][Full Text] [Related]
10. ETUNet:Exploring efficient transformer enhanced UNet for 3D brain tumor segmentation.
Zhang W; Chen S; Ma Y; Liu Y; Cao X
Comput Biol Med; 2024 Mar; 171():108005. PubMed ID: 38340437
[TBL] [Abstract][Full Text] [Related]
11. TGDAUNet: Transformer and GCNN based dual-branch attention UNet for medical image segmentation.
Song P; Li J; Fan H; Fan L
Comput Biol Med; 2023 Dec; 167():107583. PubMed ID: 37890420
[TBL] [Abstract][Full Text] [Related]
12. LM-Net: A light-weight and multi-scale network for medical image segmentation.
Lu Z; She C; Wang W; Huang Q
Comput Biol Med; 2024 Jan; 168():107717. PubMed ID: 38007973
[TBL] [Abstract][Full Text] [Related]
13. SDResU-Net: Separable and Dilated Residual U-Net for MRI Brain Tumor Segmentation.
Zhang J; Lv X; Sun Q; Zhang Q; Wei X; Liu B
Curr Med Imaging; 2020; 16(6):720-728. PubMed ID: 32723244
[TBL] [Abstract][Full Text] [Related]
14. SGEResU-Net for brain tumor segmentation.
Liu D; Sheng N; He T; Wang W; Zhang J; Zhang J
Math Biosci Eng; 2022 Mar; 19(6):5576-5590. PubMed ID: 35603369
[TBL] [Abstract][Full Text] [Related]
15. Attention-guided multi-scale context aggregation network for multi-modal brain glioma segmentation.
Wu S; Cao Y; Li X; Liu Q; Ye Y; Liu X; Zeng L; Tian M
Med Phys; 2023 Dec; 50(12):7629-7640. PubMed ID: 37151131
[TBL] [Abstract][Full Text] [Related]
16. SC-Net: Symmetrical conical network for colorectal pathology image segmentation.
Zhang G; He Z; Zhang Y; Li Z; Wu L
Comput Methods Programs Biomed; 2024 May; 248():108119. PubMed ID: 38520785
[TBL] [Abstract][Full Text] [Related]
17. mResU-Net: multi-scale residual U-Net-based brain tumor segmentation from multimodal MRI.
Li P; Li Z; Wang Z; Li C; Wang M
Med Biol Eng Comput; 2024 Mar; 62(3):641-651. PubMed ID: 37981627
[TBL] [Abstract][Full Text] [Related]
18. MVFusFra: A Multi-View Dynamic Fusion Framework for Multimodal Brain Tumor Segmentation.
Ding Y; Zheng W; Geng J; Qin Z; Choo KR; Qin Z; Hou X
IEEE J Biomed Health Inform; 2022 Apr; 26(4):1570-1581. PubMed ID: 34699375
[TBL] [Abstract][Full Text] [Related]
19. DCU-Net: Multi-scale U-Net for brain tumor segmentation.
Yang T; Zhou Y; Li L; Zhu C
J Xray Sci Technol; 2020; 28(4):709-726. PubMed ID: 32444591
[TBL] [Abstract][Full Text] [Related]
20. HDC-Net: Hierarchical Decoupled Convolution Network for Brain Tumor Segmentation.
Luo Z; Jia Z; Yuan Z; Peng J
IEEE J Biomed Health Inform; 2021 Mar; 25(3):737-745. PubMed ID: 32750914
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
