:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Yichao, Shao, Zongru, Teng, Yueyang, Guo, Junwen
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2601.14180
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rethinking Cross-Dose PET Denoising: Mitigating Averaging Effects via Residual Noise Learning
by: Liu, Yichao, et al.
Published: (2026)

Hybrid Swin Attention Networks for Simultaneously Low-Dose PET and CT Denoising
by: Liu, Yichao, et al.
Published: (2025)

FrequencyCT: Frequency Domain Self-supervised Low-dose CT Denoising
by: Wei, Guoquan, et al.
Published: (2026)

WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT Denoising
by: Zhao, Haoyu, et al.
Published: (2024)

Learnable Total Variation with Lambda Mapping for Low-Dose CT Denoising
by: Basak, Yusuf Talha, et al.
Published: (2025)

Neighbor2Inverse: Self-Supervised Denoising for Low-Dose Region-of-Interest Phase Contrast CT
by: Thalhammer, Johannes B., et al.
Published: (2026)

FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising
by: Chen, Zhihao, et al.
Published: (2025)

On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting
by: Wagner, Fabian, et al.
Published: (2022)

Projection Guided Personalized Federated Learning for Low Dose CT Denoising
by: Zafar, Anas, et al.
Published: (2026)

BioAtt: Anatomical Prior Driven Low-Dose CT Denoising
by: Kim, Namhun, et al.
Published: (2025)

Cascaded Convolutional Neural Networks with Perceptual Loss for Low Dose CT Denoising
by: Ataei, Sepehr, et al.
Published: (2020)

PPORLD-EDNetLDCT: A Proximal Policy Optimization-Based Reinforcement Learning Framework for Adaptive Low-Dose CT Denoising
by: Sutradhar, Debopom, et al.
Published: (2025)

Extendable Generalization Self-Supervised Diffusion for Low-Dose CT Reconstruction
by: Wei, Guoquan, et al.
Published: (2025)

Self-Supervised Training For Low Dose CT Reconstruction
by: Unal, Mehmet Ozan, et al.
Published: (2020)

MID: A Self-supervised Multimodal Iterative Denoising Framework
by: Nie, Chang, et al.
Published: (2025)

Anatomy-Aware Low-Dose CT Denoising via Pretrained Vision Models and Semantic-Guided Contrastive Learning
by: Wang, Runze, et al.
Published: (2025)

Blind-Spot Guided Diffusion for Self-supervised Real-World Denoising
by: Cheng, Shen, et al.
Published: (2025)

Self is the Best Learner: CT-free Ultra-Low-Dose PET Organ Segmentation via Collaborating Denoising and Segmentation Learning
by: Ye, Zanting, et al.
Published: (2025)

Patch Triplet Similarity Purification for Guided Real-World Low-Dose CT Image Denoising
by: Long, Junhao, et al.
Published: (2025)

TAFG-MAN: Timestep-Adaptive Frequency-Gated Latent Diffusion for Efficient and High-Quality Low-Dose CT Image Denoising
by: Fang, Tangtangfang, et al.
Published: (2026)

MAN: Latent Diffusion Enhanced Multistage Anti-Noise Network for Efficient and High-Quality Low-Dose CT Image Denoising
by: Fang, Tangtangfang, et al.
Published: (2025)

D-PerceptCT: Deep Perceptual Enhancement for Low-Dose CT Images
by: Nabila, Taifour Yousra, et al.
Published: (2025)

IPv2: An Improved Image Purification Strategy for Real-World Ultra-Low-Dose Lung CT Denoising
by: Gong, Guoliang, et al.
Published: (2026)

Unsupervised Denoising of Real Clinical Low Dose Liver CT with Perceptual Attention Networks
by: Guan, Zhilin, et al.
Published: (2026)

Enhanced Low-Dose CT Image Reconstruction by Domain and Task Shifting Gaussian Denoisers
by: Selig, Tim, et al.
Published: (2024)

A Denoising Framework for Real-World Ultra-Low-Dose Lung CT Images Based on an Image Purification Strategy
by: Gong, Guoliang, et al.
Published: (2025)

Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning
by: Zhang, Yabin, et al.
Published: (2022)

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume
by: Liu, Xiwei, et al.
Published: (2024)

Score-based Self-supervised MRI Denoising
by: Tu, Jiachen, et al.
Published: (2025)

Screener: Self-supervised Pathology Segmentation in Medical CT Images
by: Goncharov, Mikhail, et al.
Published: (2025)

MAP-Diff: Multi-Anchor Guided Diffusion for Progressive 3D Whole-Body Low-Dose PET Denoising
by: Jing, Peiyuan, et al.
Published: (2026)

Task-Adaptive Low-Dose CT Reconstruction
by: Sefercioglu, Necati, et al.
Published: (2025)

Filter2Noise: A Framework for Interpretable and Zero-Shot Low-Dose CT Image Denoising
by: Sun, Yipeng, et al.
Published: (2025)

CURVETE: Curriculum Learning and Progressive Self-supervised Training for Medical Image Classification
by: Abbas, Asmaa, et al.
Published: (2025)

Weakly supervised alignment and registration of MR-CT for cervical cancer radiotherapy
by: Zhang, Jjahao, et al.
Published: (2024)

CheXLearner: Text-Guided Fine-Grained Representation Learning for Progression Detection
by: Wang, Yuanzhuo, et al.
Published: (2025)

Low-Trace Adaptation of Zero-shot Self-supervised Blind Image Denoising
by: Hu, Jintong, et al.
Published: (2024)

Self-supervised Depth Denoising Using Lower- and Higher-quality RGB-D sensors
by: Shabanov, Akhmedkhan, et al.
Published: (2020)

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging
by: Huang, Lijie, et al.
Published: (2025)

Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI
by: Zhong, Xinliu, et al.
Published: (2025)