Copertina

Deep kernel representations of latent space features for low-dose PET-MR imaging robust to variable dose reduction

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pain, Cameron Dennis, George, Yasmeen, Fornito, Alex, Egan, Gary, Chen, Zhaolin
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Motion-Informed Deep Learning for Brain MR Image Reconstruction Framework
di: Chen, Zhifeng, et al.
Pubblicazione: (2024)

PFCM: Poisson flow consistency models for low-dose CT image denoising
di: Hein, Dennis, et al.
Pubblicazione: (2024)

4D-MISR: A unified model for low-dose super-resolution imaging via feature fusion
di: Wang, Zifei, et al.
Pubblicazione: (2025)

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction
di: Geng, Mengxiao, et al.
Pubblicazione: (2025)

Full-dose Whole-body PET Synthesis from Low-dose PET Using High-efficiency Denoising Diffusion Probabilistic Model: PET Consistency Model
di: Pan, Shaoyan, et al.
Pubblicazione: (2023)

End-to-end Triple-domain PET Enhancement: A Hybrid Denoising-and-reconstruction Framework for Reconstructing Standard-dose PET Images from Low-dose PET Sinograms
di: Jiang, Caiwen, et al.
Pubblicazione: (2024)

Multipath cycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels
di: Krishnan, Aravind R., et al.
Pubblicazione: (2025)

Diffusion Transformer Model With Compact Prior for Low-dose PET Reconstruction
di: Huang, Bin, et al.
Pubblicazione: (2024)

CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction
di: Ekanayake, Mevan, et al.
Pubblicazione: (2023)

SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution
di: Ekanayake, Mevan, et al.
Pubblicazione: (2024)

Low‐dose PET/MR image enhancement using deep learning with an MR‐based anatomical structure attention mechanism
di: Yunqi Zhang, et al.
Pubblicazione: (2025)

DenoMamba: A fused state-space model for low-dose CT denoising
di: Öztürk, Şaban, et al.
Pubblicazione: (2024)

S3PET: Semi-supervised Standard-dose PET Image Reconstruction via Dose-aware Token Swap
di: Cui, Jiaqi, et al.
Pubblicazione: (2024)

Towards order of magnitude X-ray dose reduction in breast cancer imaging using phase contrast and deep denoising
di: Pakzad, Ashkan, et al.
Pubblicazione: (2025)

Gadolinium dose reduction for brain MRI using conditional deep learning
di: Pinetz, Thomas, et al.
Pubblicazione: (2024)

Meta-information Guided Cross-domain Synergistic Diffusion Model for Low-dose PET Reconstruction
di: Geng, Mengxiao, et al.
Pubblicazione: (2025)

M2Diff: Multi-Modality Multi-Task Enhanced Diffusion Model for MRI-Guided Low-Dose PET Enhancement
di: Yar, Ghulam Nabi Ahmad Hassan, et al.
Pubblicazione: (2026)

Learning predictable and robust neural representations by straightening image sequences
di: Niu, Xueyan, et al.
Pubblicazione: (2024)

Low-dose CT Denoising with Language-engaged Dual-space Alignment
di: Chen, Zhihao, et al.
Pubblicazione: (2024)

Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction
di: Webber, George, et al.
Pubblicazione: (2025)

Full‐dose whole‐body PET synthesis from low‐dose PET using high‐efficiency denoising diffusion probabilistic model: PET consistency model
di: Shaoyan Pan, et al.
Pubblicazione: (2024)

Domain-invariant feature learning in brain MR imaging for content-based image retrieval
di: Tobari, Shuya, et al.
Pubblicazione: (2025)

Patient-specific radiomic feature selection with reconstructed healthy persona of knee MR images
di: Chen, Yaxi, et al.
Pubblicazione: (2025)

Polaffini: A feature-based approach for robust affine and polyaffine image registration
di: Legouhy, Antoine, et al.
Pubblicazione: (2026)

Learning deep illumination-robust features from multispectral filter array images
di: Amziane, Anis
Pubblicazione: (2024)

Denoising Low-dose Images Using Deep Learning of Time Series Images
di: Shao, Yang, et al.
Pubblicazione: (2024)

Counterfactual contrastive learning: robust representations via causal image synthesis
di: Roschewitz, Melanie, et al.
Pubblicazione: (2024)

FeatMap: Understanding image manipulation in the feature space and its implications for feature space geometry
di: Krey, Elias B., et al.
Pubblicazione: (2026)

Noise‐assisted hybrid attention networks for low‐dose PET and CT denoising
di: Hengzhi Xue, et al.
Pubblicazione: (2024)

On characterizing X-ray detectors for low-dose imaging
di: Sakhatskyi, Kostiantyn, et al.
Pubblicazione: (2024)

Exploring PCA-based feature representations of image pixels via CNN to enhance food image segmentation
di: Dai, Ying
Pubblicazione: (2024)

CT image denoising methods for image quality improvement and radiation dose reduction
di: Rabeya Tus Sadia, et al.
Pubblicazione: (2024)

Epanechnikov nonparametric kernel density estimation based feature-learning in respiratory disease chest X-ray images
di: Marsico, Veronica, et al.
Pubblicazione: (2025)

Deep learning based super‐resolution for CBCT dose reduction in radiotherapy
di: Adrian Thummerer, et al.
Pubblicazione: (2024)

PatchDenoiser: Parameter-efficient multi-scale patch learning and fusion denoiser for Low-dose CT imaging
di: Fartiyal, Jitindra, et al.
Pubblicazione: (2026)

Effect of immobilization mask and beam energy on dose coverage to small joints in treating osteoarthritis with low‐dose radiation therapy
di: George X. Ding, et al.
Pubblicazione: (2025)

Evaluating Adversarial Robustness of Low dose CT Recovery
di: Gandikota, Kanchana Vaishnavi, et al.
Pubblicazione: (2024)

UR‐cycleGAN: Denoising full‐body low‐dose PET images using cycle‐consistent Generative Adversarial Networks
di: Yang Liu, et al.
Pubblicazione: (2025)

PushPull-Net: Inhibition-driven ResNet robust to image corruptions
di: Bennabhaktula, Guru Swaroop, et al.
Pubblicazione: (2024)

Structure-Guided MR-to-CT Synthesis with Spatial and Semantic Alignments for Attenuation Correction of Whole-Body PET/MR Imaging
di: Zheng, Jiaxu, et al.
Pubblicazione: (2024)