SelfCoLearn: Self-Supervised Collaborative Learning for Accelerating Dynamic MR Imaging

SelfCoLearn: Self-Supervised Collaborative Learning for Accelerating Dynamic MR Imaging

Lately, deep learning technology has been extensively investigated for accelerating dynamic magnetic resonance (MR) imaging, with encouraging progresses achieved. However, without fully sampled reference data for training, the current approaches may have limited abilities in recovering fine details...

Full description

Bibliographic Details
Main Authors:	Juan Zou, Cheng Li, Sen Jia, Ruoyou Wu, Tingrui Pei, Hairong Zheng, Shanshan Wang
Format:	Article
Language:	English
Published:	MDPI AG 2022-11-01
Series:	Bioengineering
Subjects:	dynamic MR imaging self-supervised learning collaborative learning reunderampling data augmentation co-training loss
Online Access:	https://www.mdpi.com/2306-5354/9/11/650

Similar Items

A novel collaborative self-supervised learning method for radiomic data
by: Zhiyuan Li, et al.
Published: (2023-08-01)

MV–MR: Multi-Views and Multi-Representations for Self-Supervised Learning and Knowledge Distillation
by: Vitaliy Kinakh, et al.
Published: (2024-05-01)

Self-Supervised and Few-Shot Contrastive Learning Frameworks for Text Clustering
by: Haoxiang Shi, et al.
Published: (2023-01-01)

ViewMix: Augmentation for Robust Representation in Self-Supervised Learning
by: Arjon Das, et al.
Published: (2024-01-01)

Self-Supervised Action Representation Learning Based on Asymmetric Skeleton Data Augmentation
by: Hualing Zhou, et al.
Published: (2022-11-01)

Self-Supervised Learning for Industrial Image Anomaly Detection by Simulating Anomalous Samples
by: Mingjing Pei, et al.
Published: (2023-09-01)

WaveBYOL: Self-Supervised Learning for Audio Representation From Raw Waveforms
by: Sunghyun Kim, et al.
Published: (2023-01-01)

Self-Supervised Learning-For Underwater Acoustic Signal Classification With Mixup
by: Qisheng Xu, et al.
Published: (2024-01-01)

Balancing the Scale: Data Augmentation Techniques for Improved Supervised Learning in Cyberattack Detection
by: Kateryna Medvedieva, et al.
Published: (2024-09-01)

Self-supervised learning for macromolecular structure classification based on cryo-electron tomograms
by: Tarun Gupta, et al.
Published: (2022-08-01)

Transfer learning application of self-supervised learning in ARPES
by: Sandy Adhitia Ekahana, et al.
Published: (2023-01-01)

Survey on Self-Supervised Learning: Auxiliary Pretext Tasks and Contrastive Learning Methods in Imaging
by: Saleh Albelwi
Published: (2022-04-01)

Automated Screening of Precancerous Cervical Cells Through Contrastive Self-Supervised Learning
by: Jaewoo Chun, et al.
Published: (2024-11-01)

From Self-supervised Learning to Transfer Learning with Musculoskeletal Radiographs
by: Hinterwimmer Florian, et al.
Published: (2022-09-01)

Multi-Augmentation-Based Contrastive Learning for Semi-Supervised Learning
by: Jie Wang, et al.
Published: (2024-02-01)

Multi-Task Collaborative Network: Bridge the Supervised and Self-Supervised Learning for EEG Classification in RSVP Tasks
by: Hongxin Li, et al.
Published: (2024-01-01)

Investigating Contrastive Pair Learning’s Frontiers in Supervised, Semisupervised, and Self-Supervised Learning
by: Bihi Sabiri, et al.
Published: (2024-08-01)

Collaborative Learning-Based Network for Weakly Supervised Remote Sensing Object Detection
by: Suting Chen, et al.
Published: (2023-01-01)

Unsupervised Visual Anomaly Detection Using Self-Supervised Pre-Trained Transformer
by: Jun-Hyung Kim, et al.
Published: (2024-01-01)

Multi-Agent Multi-View Collaborative Perception Based on Semi-Supervised Online Evolutive Learning
by: Di Li, et al.
Published: (2022-09-01)

Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation
by: Feng Wei, et al.
Published: (2024-12-01)

Investigation of semi- and self-supervised learning methods in the histopathological domain
by: Benjamin Voigt, et al.
Published: (2023-01-01)

Image-Based Vehicle Classification by Synergizing Features from Supervised and Self-Supervised Learning Paradigms
by: Shihan Ma, et al.
Published: (2023-02-01)

Supervised and Self-Supervised Learning for Assembly Line Action Recognition
by: Christopher Indris, et al.
Published: (2025-01-01)

Self-Supervised Learning across the Spectrum
by: Jayanth Shenoy, et al.
Published: (2024-09-01)

An improved self-supervised learning for EEG classification
by: Yanghan Ou, et al.
Published: (2022-05-01)

DimCL: Dimensional Contrastive Learning for Improving Self-Supervised Learning
by: Thanh Nguyen, et al.
Published: (2023-01-01)

Temporal and spatial self supervised learning methods for electrocardiograms
by: Wenping Chen, et al.
Published: (2025-02-01)

Self-Supervised Learning for Solar Radio Spectrum Classification
by: Siqi Li, et al.
Published: (2022-12-01)

Traffic Prediction with Self-Supervised Learning: A Heterogeneity-Aware Model for Urban Traffic Flow Prediction Based on Self-Supervised Learning
by: Min Gao, et al.
Published: (2024-04-01)

Hierarchical Self-Supervised Learning for Knowledge-Aware Recommendation
by: Cong Zhou, et al.
Published: (2024-10-01)

Decoupled self-supervised label augmentation for fully-supervised image classification
by: Gao, Wanshun, et al.
Published: (2024)

A Survey on Contrastive Self-Supervised Learning
by: Ashish Jaiswal, et al.
Published: (2020-12-01)

Rethinking Pseudo-Labeling for Semi-Supervised Facial Expression Recognition With Contrastive Self-Supervised Learning
by: Bei Fang, et al.
Published: (2023-01-01)

Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition: A Review
by: Hui Chen, et al.
Published: (2024-01-01)

Review of Self-supervised Learning Methods in Field of ECG
by: HAN Han, HUANG Xunhua, CHANG Huihui, FAN Haoyi, CHEN Peng, CHEN Jijia
Published: (2024-07-01)

Experimental Case Study of Self-Supervised Learning for Voice Spoofing Detection
by: Yerin Lee, et al.
Published: (2023-01-01)

Intra-video positive pairs in self-supervised learning for ultrasound
by: Blake VanBerlo, et al.
Published: (2024-06-01)

Mobility-aware federated self-supervised learning in vehicular network
by: Xueying Gu, et al.
Published: (2024-09-01)

Adaptive Safe Semi-Supervised Extreme Machine Learning
by: Jun Ma, et al.
Published: (2019-01-01)