Buchumschlag

Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Oliveira, Guilherme C., Rosa, Gustavo H., Pedronette, Daniel C. G., Papa, João P., Kumar, Himeesh, Passos, Leandro A., Kumar, Dinesh
Format:	Preprint
Veröffentlicht:	2022
Schlagworte:	Image and Video Processing Computer Vision and Pattern Recognition Machine Learning
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Oral squamous cell detection using deep learning
von: Sharma, Samrat Kumar Dev
Veröffentlicht: (2024)

Improving the generalization of deep learning models in the segmentation of mammography images
von: Hurtado, Jan, et al.
Veröffentlicht: (2025)

High-resolution single-pixel imaging in real time with iterative or deep learning-based reconstruction enhancement
von: Pastuszczak, Anna, et al.
Veröffentlicht: (2025)

Hyperspectral image reconstruction by deep learning with super-Rayleigh speckles
von: Chen, Ziyan, et al.
Veröffentlicht: (2025)

Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases
von: Muthukumar, K. A., et al.
Veröffentlicht: (2025)

Quality assessment of brain structural MR images: Comparing generalization of deep learning versus hand-crafted feature-based machine learning methods to new sites
von: Kaur, Prabhjot, et al.
Veröffentlicht: (2026)

Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning
von: Wang, Shanshan, et al.
Veröffentlicht: (2024)

Generative MR Multitasking with complex-harmonic cardiac encoding: Bridging the gap between gated imaging and real-time imaging
von: Fang, Xinguo, et al.
Veröffentlicht: (2025)

Towards optimal multimode fiber imaging by leveraging input polarization and deep learning
von: Maqbool, Jawaria, et al.
Veröffentlicht: (2023)

FGR-Net:Interpretable fundus imagegradeability classification based on deepreconstruction learning
von: Khalid, Saif, et al.
Veröffentlicht: (2024)

Diffusion model for gradient preconditioning in hyperspectral imaging inverse problems
von: Monsalve, Jonathan, et al.
Veröffentlicht: (2025)

A multi-dynamic low-rank deep image prior (ML-DIP) for 3D real-time cardiovascular MRI
von: Chen, Chong, et al.
Veröffentlicht: (2025)

EdgeSRIE: A hybrid deep learning framework for real-time speckle reduction and image enhancement on portable ultrasound systems
von: Cho, Hyunwoo, et al.
Veröffentlicht: (2025)

TransUNext: towards a more advanced U-shaped framework for automatic vessel segmentation in the fundus image
von: Li, Xiang, et al.
Veröffentlicht: (2024)

MAM-E: Mammographic synthetic image generation with diffusion models
von: Montoya-del-Angel, Ricardo, et al.
Veröffentlicht: (2023)

GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models
von: Zotova, Daria, et al.
Veröffentlicht: (2025)

$μ$GUIDE: a framework for quantitative imaging via generalized uncertainty-driven inference using deep learning
von: Jallais, Maëliss, et al.
Veröffentlicht: (2023)

SYNTA: A novel approach for deep learning-based image analysis in muscle histopathology using photo-realistic synthetic data
von: Mill, Leonid, et al.
Veröffentlicht: (2022)

SPASHT: An image-enhancement method for sparse-view MPI SPECT
von: Yang, Zezhang, et al.
Veröffentlicht: (2025)

Rethinking domain generalization in medical image segmentation: One image as one domain
von: Hong, Jin, et al.
Veröffentlicht: (2025)

Merging synthetic and real embryo data for advanced AI predictions
von: Presacan, Oriana, et al.
Veröffentlicht: (2024)

Meta-learners for few-shot weakly-supervised optic disc and cup segmentation on fundus images
von: Zumarsyah, Pandega Abyan, et al.
Veröffentlicht: (2025)

Characterizing segregation in blast rock piles a deep-learning approach leveraging aerial image analysis
von: Liu, Chengeng, et al.
Veröffentlicht: (2024)

Using a modified double deep image prior for crosstalk mitigation in multislice ptychography
von: Du, Ming, et al.
Veröffentlicht: (2021)

Equitable non-contact infrared thermography after solar loading using deep learning
von: Zhao, Ellin Q., et al.
Veröffentlicht: (2023)

200mm Optical synthetic aperture imaging over 120 meters distance via Macroscopic Fourier ptychography
von: Zhang, Qi, et al.
Veröffentlicht: (2023)

Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium
von: Shuaib, Haris, et al.
Veröffentlicht: (2024)

Enhancing crop classification accuracy by synthetic SAR-Optical data generation using deep learning
von: Mirzaei, Ali, et al.
Veröffentlicht: (2024)

A graph neural network-based multispectral-view learning model for diabetic macular ischemia detection from color fundus photographs
von: He, Qinghua, et al.
Veröffentlicht: (2025)

Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement
von: Lee, Ho Hin, et al.
Veröffentlicht: (2024)

Limited-angle SPECT image reconstruction using deep image prior
von: Hori, Kensuke, et al.
Veröffentlicht: (2025)

Self-supervised feature learning for cardiac Cine MR image reconstruction
von: Xu, Siying, et al.
Veröffentlicht: (2025)

Malaria detection using Deep Convolution Neural Network
von: Kumar, Sumit, et al.
Veröffentlicht: (2023)

Self-supervised learning improves robustness of deep learning lung tumor segmentation to CT imaging differences
von: Jiang, Jue, et al.
Veröffentlicht: (2024)

Confidence-aware multi-modality learning for eye disease screening
von: Zou, Ke, et al.
Veröffentlicht: (2024)

Comparing DWI image quality of deep-learning-reconstructed EPI with RESOLVE in breast lesions at 3.0T: a pilot study
von: Tsarouchi, Marialena I., et al.
Veröffentlicht: (2024)

A 3D deep learning classifier and its explainability when assessing coronary artery disease
von: Cheung, Wing Keung, et al.
Veröffentlicht: (2023)

mAIstro: an open-source multi-agentic system for automated end-to-end development of radiomics and deep learning models for medical imaging
von: Tzanis, Eleftherios, et al.
Veröffentlicht: (2025)

Image guidance in deep brain stimulation surgery to treat Parkinson's disease: a review
von: Xiao, Yiming, et al.
Veröffentlicht: (2020)

Classification based deep learning models for lung cancer and disease using medical images
von: Chaddad, Ahmad, et al.
Veröffentlicht: (2025)