These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
173 related articles for article (PubMed ID: 38343216)
1. A Deep Learning-Based Approach for Cervical Cancer Classification Using 3D CNN and Vision Transformer. K A; B S J Imaging Inform Med; 2024 Feb; 37(1):280-296. PubMed ID: 38343216 [TBL] [Abstract][Full Text] [Related]
2. 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]
3. A VGG attention vision transformer network for benign and malignant classification of breast ultrasound images. Qu X; Lu H; Tang W; Wang S; Zheng D; Hou Y; Jiang J Med Phys; 2022 Sep; 49(9):5787-5798. PubMed ID: 35866492 [TBL] [Abstract][Full Text] [Related]
4. Conv-Swinformer: Integration of CNN and shift window attention for Alzheimer's disease classification. Hu Z; Li Y; Wang Z; Zhang S; Hou W; Comput Biol Med; 2023 Sep; 164():107304. PubMed ID: 37549456 [TBL] [Abstract][Full Text] [Related]
5. DLNLF-net: Denoised local and non-local deep features fusion network for malignancy characterization of hepatocellular carcinoma. Huang H; Xie Y; Wang G; Zhang L; Zhou W Comput Methods Programs Biomed; 2022 Dec; 227():107201. PubMed ID: 36335751 [TBL] [Abstract][Full Text] [Related]
6. Plant-CNN-ViT: Plant Classification with Ensemble of Convolutional Neural Networks and Vision Transformer. Lee CP; Lim KM; Song YX; Alqahtani A Plants (Basel); 2023 Jul; 12(14):. PubMed ID: 37514256 [TBL] [Abstract][Full Text] [Related]
7. fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations. Vu H; Kim HC; Jung M; Lee JH Neuroimage; 2020 Dec; 223():117328. PubMed ID: 32896633 [TBL] [Abstract][Full Text] [Related]
8. Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System. Himel GMS; Islam MM; Al-Aff KA; Karim SI; Sikder MKU Int J Biomed Imaging; 2024; 2024():3022192. PubMed ID: 38344227 [TBL] [Abstract][Full Text] [Related]
9. A deep dive into understanding tumor foci classification using multiparametric MRI based on convolutional neural network. Zong W; Lee JK; Liu C; Carver EN; Feldman AM; Janic B; Elshaikh MA; Pantelic MV; Hearshen D; Chetty IJ; Movsas B; Wen N Med Phys; 2020 Sep; 47(9):4077-4086. PubMed ID: 32449176 [TBL] [Abstract][Full Text] [Related]
10. Swin-GA-RF: genetic algorithm-based Swin Transformer and random forest for enhancing cervical cancer classification. Alohali MA; El-Rashidy N; Alaklabi S; Elmannai H; Alharbi S; Saleh H Front Oncol; 2024; 14():1392301. PubMed ID: 39099689 [TBL] [Abstract][Full Text] [Related]
11. Squeeze-and-excitation-attention-based mobile vision transformer for grading recognition of bladder prolapse in pelvic MRI images. Zhu S; Chen G; Chen H; Lu Y; Wu M; Zheng B; Liu D; Qian C; Chen Y Med Phys; 2024 Aug; 51(8):5236-5249. PubMed ID: 38767532 [TBL] [Abstract][Full Text] [Related]
12. ViT-PSO-SVM: Cervical Cancer Predication Based on Integrating Vision Transformer with Particle Swarm Optimization and Support Vector Machine. AlMohimeed A; Shehata M; El-Rashidy N; Mostafa S; Samy Talaat A; Saleh H Bioengineering (Basel); 2024 Jul; 11(7):. PubMed ID: 39061811 [TBL] [Abstract][Full Text] [Related]
13. CVTrack: Combined Convolutional Neural Network and Vision Transformer Fusion Model for Visual Tracking. Wang J; Song Y; Song C; Tian H; Zhang S; Sun J Sensors (Basel); 2024 Jan; 24(1):. PubMed ID: 38203136 [TBL] [Abstract][Full Text] [Related]
14. A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss. Nie Y; Sommella P; Carratù M; O'Nils M; Lundgren J Diagnostics (Basel); 2022 Dec; 13(1):. PubMed ID: 36611363 [TBL] [Abstract][Full Text] [Related]
15. Conv-ViT: A Convolution and Vision Transformer-Based Hybrid Feature Extraction Method for Retinal Disease Detection. Dutta P; Sathi KA; Hossain MA; Dewan MAA J Imaging; 2023 Jul; 9(7):. PubMed ID: 37504817 [TBL] [Abstract][Full Text] [Related]
16. 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]
17. ssFPN: Scale Sequence ( Park HJ; Kang JW; Kim BG Sensors (Basel); 2023 Apr; 23(9):. PubMed ID: 37177636 [TBL] [Abstract][Full Text] [Related]
18. TPFR-Net: U-shaped model for lung nodule segmentation based on transformer pooling and dual-attention feature reorganization. Li X; Jiang A; Qiu Y; Li M; Zhang X; Yan S Med Biol Eng Comput; 2023 Aug; 61(8):1929-1946. PubMed ID: 37243853 [TBL] [Abstract][Full Text] [Related]
19. HTC-retina: A hybrid retinal diseases classification model using transformer-Convolutional Neural Network from optical coherence tomography images. Laouarem A; Kara-Mohamed C; Bourennane EB; Hamdi-Cherif A Comput Biol Med; 2024 Aug; 178():108726. PubMed ID: 38878400 [TBL] [Abstract][Full Text] [Related]
20. SwinCross: Cross-modal Swin transformer for head-and-neck tumor segmentation in PET/CT images. Li GY; Chen J; Jang SI; Gong K; Li Q Med Phys; 2024 Mar; 51(3):2096-2107. PubMed ID: 37776263 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]