402 related articles for article (PubMed ID: 36215583)
1. Fusion network based on the dual attention mechanism and atrous spatial pyramid pooling for automatic segmentation in retinal vessel images.
Liang B; Tang C; Xu M; Wu T; Lei Z
J Opt Soc Am A Opt Image Sci Vis; 2022 Aug; 39(8):1393-1402. PubMed ID: 36215583
[TBL] [Abstract][Full Text] [Related]
2. Multi-scale retinal vessel segmentation using encoder-decoder network with squeeze-and-excitation connection and atrous spatial pyramid pooling.
Xie H; Tang C; Zhang W; Shen Y; Lei Z
Appl Opt; 2021 Jan; 60(2):239-249. PubMed ID: 33448945
[TBL] [Abstract][Full Text] [Related]
3. A multiple-channel and atrous convolution network for ultrasound image segmentation.
Zhang L; Zhang J; Li Z; Song Y
Med Phys; 2020 Dec; 47(12):6270-6285. PubMed ID: 33007105
[TBL] [Abstract][Full Text] [Related]
4. Lightweight pyramid network with spatial attention mechanism for accurate retinal vessel segmentation.
Tan T; Wang Z; Du H; Xu J; Qiu B
Int J Comput Assist Radiol Surg; 2021 Apr; 16(4):673-682. PubMed ID: 33751370
[TBL] [Abstract][Full Text] [Related]
5. Dual-path multi-scale context dense aggregation network for retinal vessel segmentation.
Zhou W; Bai W; Ji J; Yi Y; Zhang N; Cui W
Comput Biol Med; 2023 Sep; 164():107269. PubMed ID: 37562323
[TBL] [Abstract][Full Text] [Related]
6. Developing a Novel Methodology by Integrating Deep Learning and HMM for Segmentation of Retinal Blood Vessels in Fundus Images.
Hassan M; Ali S; Kim JY; Saadia A; Sanaullah M; Alquhayz H; Safdar K
Interdiscip Sci; 2023 Jun; 15(2):273-292. PubMed ID: 36611082
[TBL] [Abstract][Full Text] [Related]
7. SFA-Net: Scale and Feature Aggregate Network for Retinal Vessel Segmentation.
Ni J; Liu J; Li X; Chen Z
J Healthc Eng; 2022; 2022():4695136. PubMed ID: 36312595
[TBL] [Abstract][Full Text] [Related]
8. SegR-Net: A deep learning framework with multi-scale feature fusion for robust retinal vessel segmentation.
Ryu J; Rehman MU; Nizami IF; Chong KT
Comput Biol Med; 2023 Sep; 163():107132. PubMed ID: 37343468
[TBL] [Abstract][Full Text] [Related]
9. UNet retinal blood vessel segmentation algorithm based on improved pyramid pooling method and attention mechanism.
Du XF; Wang JS; Sun WZ
Phys Med Biol; 2021 Aug; 66(17):. PubMed ID: 34375955
[TBL] [Abstract][Full Text] [Related]
10. [Lung parenchyma segmentation based on double scale parallel attention network].
Feng K; Ren L; Wu Y; Li Y; Wang H; Wang G
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2022 Aug; 39(4):721-729. PubMed ID: 36008336
[TBL] [Abstract][Full Text] [Related]
11. Deep Neural Network-Based Semantic Segmentation of Microvascular Decompression Images.
Bai R; Jiang S; Sun H; Yang Y; Li G
Sensors (Basel); 2021 Feb; 21(4):. PubMed ID: 33562275
[TBL] [Abstract][Full Text] [Related]
12. MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation.
Li J; Zhang T; Zhao Y; Chen N; Zhou H; Xu H; Guan Z; Xue L; Yang C; Chen R; Wei L
Comput Intell Neurosci; 2022; 2022():9917691. PubMed ID: 36387767
[TBL] [Abstract][Full Text] [Related]
13. MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images.
Balraj K; Ramteke M; Mittal S; Bhargava R; Rathore AS
Sci Rep; 2024 Jun; 14(1):12699. PubMed ID: 38830932
[TBL] [Abstract][Full Text] [Related]
14. MCFSA-Net: A multi-scale channel fusion and spatial activation network for retinal vessel segmentation.
Li R; Li Z; Fan H; Teng S; Cao X
J Biophotonics; 2023 Apr; 16(4):e202200295. PubMed ID: 36413066
[TBL] [Abstract][Full Text] [Related]
15. MTPA_Unet: Multi-Scale Transformer-Position Attention Retinal Vessel Segmentation Network Joint Transformer and CNN.
Jiang Y; Liang J; Cheng T; Lin X; Zhang Y; Dong J
Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746372
[TBL] [Abstract][Full Text] [Related]
16. CE-Net: Context Encoder Network for 2D Medical Image Segmentation.
Gu Z; Cheng J; Fu H; Zhou K; Hao H; Zhao Y; Zhang T; Gao S; Liu J
IEEE Trans Med Imaging; 2019 Oct; 38(10):2281-2292. PubMed ID: 30843824
[TBL] [Abstract][Full Text] [Related]
17. GourmetNet: Food Segmentation Using Multi-Scale Waterfall Features with Spatial and Channel Attention.
Sharma U; Artacho B; Savakis A
Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833577
[TBL] [Abstract][Full Text] [Related]
18. MIC-Net: multi-scale integrated context network for automatic retinal vessel segmentation in fundus image.
Wang J; Zhou L; Yuan Z; Wang H; Shi C
Math Biosci Eng; 2023 Feb; 20(4):6912-6931. PubMed ID: 37161134
[TBL] [Abstract][Full Text] [Related]
19. Accurate Retinal Vessel Segmentation in Color Fundus Images via Fully Attention-Based Networks.
Li K; Qi X; Luo Y; Yao Z; Zhou X; Sun M
IEEE J Biomed Health Inform; 2021 Jun; 25(6):2071-2081. PubMed ID: 33001809
[TBL] [Abstract][Full Text] [Related]
20. Polyp segmentation network with hybrid channel-spatial attention and pyramid global context guided feature fusion.
Huang X; Zhuo L; Zhang H; Yang Y; Li X; Zhang J; Wei W
Comput Med Imaging Graph; 2022 Jun; 98():102072. PubMed ID: 35594809
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
