163 related articles for article (PubMed ID: 38001149)
1. Unfolded deep kernel estimation-attention UNet-based retinal image segmentation.
Radha K; Yepuganti K; Saritha S; Kamireddy C; Bavirisetti DP
Sci Rep; 2023 Nov; 13(1):20712. PubMed ID: 38001149
[TBL] [Abstract][Full Text] [Related]
2. DAVS-NET: Dense Aggregation Vessel Segmentation Network for retinal vasculature detection in fundus images.
Raza M; Naveed K; Akram A; Salem N; Afaq A; Madni HA; Khan MAU; Din MZ
PLoS One; 2021; 16(12):e0261698. PubMed ID: 34972109
[TBL] [Abstract][Full Text] [Related]
3. PCAT-UNet: UNet-like network fused convolution and transformer for retinal vessel segmentation.
Chen D; Yang W; Wang L; Tan S; Lin J; Bu W
PLoS One; 2022; 17(1):e0262689. PubMed ID: 35073371
[TBL] [Abstract][Full Text] [Related]
4. A new robust method for blood vessel segmentation in retinal fundus images based on weighted line detector and hidden Markov model.
Zhou C; Zhang X; Chen H
Comput Methods Programs Biomed; 2020 Apr; 187():105231. PubMed ID: 31786454
[TBL] [Abstract][Full Text] [Related]
5. A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model.
Gegundez-Arias ME; Marin-Santos D; Perez-Borrero I; Vasallo-Vazquez MJ
Comput Methods Programs Biomed; 2021 Jun; 205():106081. PubMed ID: 33882418
[TBL] [Abstract][Full Text] [Related]
6. TDCAU-Net: retinal vessel segmentation using transformer dilated convolutional attention-based U-Net method.
Li C; Li Z; Liu W
Phys Med Biol; 2023 Dec; 69(1):. PubMed ID: 38052089
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Segmentation of retinal vessels in fundus images based on U-Net with self-calibrated convolutions and spatial attention modules.
Rong Y; Xiong Y; Li C; Chen Y; Wei P; Wei C; Fan Z
Med Biol Eng Comput; 2023 Jul; 61(7):1745-1755. PubMed ID: 36899285
[TBL] [Abstract][Full Text] [Related]
9. Hard Attention Net for Automatic Retinal Vessel Segmentation.
Wang D; Haytham A; Pottenburgh J; Saeedi O; Tao Y
IEEE J Biomed Health Inform; 2020 Dec; 24(12):3384-3396. PubMed ID: 32750941
[TBL] [Abstract][Full Text] [Related]
10. RFARN: Retinal vessel segmentation based on reverse fusion attention residual network.
Liu W; Jiang Y; Zhang J; Ma Z
PLoS One; 2021; 16(12):e0257256. PubMed ID: 34860847
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images.
Liu Y; Shen J; Yang L; Yu H; Bian G
Comput Biol Med; 2023 Jan; 152():106341. PubMed ID: 36463794
[TBL] [Abstract][Full Text] [Related]
13. Particle swarm optimization method for small retinal vessels detection on multiresolution fundus images.
Khomri B; Christodoulidis A; Djerou L; Babahenini MC; Cheriet F
J Biomed Opt; 2018 May; 23(5):1-13. PubMed ID: 29749141
[TBL] [Abstract][Full Text] [Related]
14. MTNet: A combined diagnosis algorithm of vessel segmentation and diabetic retinopathy for retinal images.
Liu R; Gao S; Zhang H; Wang S; Zhou L; Liu J
PLoS One; 2022; 17(11):e0278126. PubMed ID: 36417405
[TBL] [Abstract][Full Text] [Related]
15. TUnet-LBF: Retinal fundus image fine segmentation model based on transformer Unet network and LBF.
Zhang H; Ni W; Luo Y; Feng Y; Song R; Wang X
Comput Biol Med; 2023 Jun; 159():106937. PubMed ID: 37084640
[TBL] [Abstract][Full Text] [Related]
16. An improved supervised and attention mechanism-based U-Net algorithm for retinal vessel segmentation.
Ma Z; Li X
Comput Biol Med; 2024 Jan; 168():107770. PubMed ID: 38056215
[TBL] [Abstract][Full Text] [Related]
17. Retinal vessel segmentation method based on RSP-SA Unet network.
Sun K; Chen Y; Dong F; Wu Q; Geng J; Chen Y
Med Biol Eng Comput; 2024 Feb; 62(2):605-620. PubMed ID: 37964177
[TBL] [Abstract][Full Text] [Related]
18. A Hybrid Unsupervised Approach for Retinal Vessel Segmentation.
Khan KB; Siddique MS; Ahmad M; Mazzara M
Biomed Res Int; 2020; 2020():8365783. PubMed ID: 33381585
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. "Keep it simple, scholar": an experimental analysis of few-parameter segmentation networks for retinal vessels in fundus imaging.
Fu W; Breininger K; Schaffert R; Pan Z; Maier A
Int J Comput Assist Radiol Surg; 2021 Jun; 16(6):967-978. PubMed ID: 33929676
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
