Buchumschlag

How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Khanal, Bidur, Bhattarai, Binod, Khanal, Bishesh, Linte, Cristian
Format:	Preprint
Veröffentlicht:	2024
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

Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification
von: Khanal, Bidur, et al.
Veröffentlicht: (2024)

Assessing the Performance of the DINOv2 Self-supervised Learning Vision Transformer Model for the Segmentation of the Left Atrium from MRI Images
von: Kundu, Bipasha, et al.
Veröffentlicht: (2024)

Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise
von: Khanal, Bidur, et al.
Veröffentlicht: (2024)

A Two Stage Pipeline for Left Atrial Wall Constrained Scar Segmentation and Localization from LGE-MR Images
von: Kundu, Bipasha, et al.
Veröffentlicht: (2026)

AI-Assisted Cervical Cancer Screening
von: Poudel, Kanchan, et al.
Veröffentlicht: (2024)

Clean self-supervised MRI reconstruction from noisy, sub-sampled training data with Robust SSDU
von: Millard, Charles, et al.
Veröffentlicht: (2022)

Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma Dataset
von: Adhikari, Bijay, et al.
Veröffentlicht: (2024)

Cross-Task Data Augmentation by Pseudo-label Generation for Region Based Coronary Artery Instance Segmentation
von: Pokhrel, Sandesh, et al.
Veröffentlicht: (2023)

A generalizable 3D framework and model for self-supervised learning in medical imaging
von: Xu, Tony, et al.
Veröffentlicht: (2025)

Multi-Scale Feature Fusion with Image-Driven Spatial Integration for Left Atrium Segmentation from Cardiac MRI Images
von: Kundu, Bipasha, et al.
Veröffentlicht: (2025)

Deep-learning Assisted Detection and Quantification of (oo)cysts of Giardia and Cryptosporidium on Smartphone Microscopy Images
von: Nakarmi, Suprim, et al.
Veröffentlicht: (2023)

Resource-efficient medical image classification for edge devices
von: Lavaei, Mahsa, et al.
Veröffentlicht: (2025)

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

Boundary Constraint-free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction
von: Yang, Zixin, et al.
Veröffentlicht: (2024)

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
von: Cerri, Stefano, et al.
Veröffentlicht: (2025)

Enhancing pretraining efficiency for medical image segmentation via transferability metrics
von: Hidy, Gábor, et al.
Veröffentlicht: (2024)

Shape-intensity knowledge distillation for robust medical image segmentation
von: Dong, Wenhui, et al.
Veröffentlicht: (2024)

Semise: Semi-supervised learning for severity representation in medical image
von: Tran, Dung T., et al.
Veröffentlicht: (2025)

A self-supervised CNN for image watermark removal
von: Tian, Chunwei, et al.
Veröffentlicht: (2024)

An effective interactive brain cytoarchitectonic parcellation framework using pretrained foundation model
von: Zhang, Shiqi, 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)

Semi-weakly-supervised neural network training for medical image registration
von: Li, Yiwen, et al.
Veröffentlicht: (2024)

Efficient onboard multi-task AI architecture based on self-supervised learning
von: Inzerillo, Gabriele, et al.
Veröffentlicht: (2024)

Enhancing image quality prediction with self-supervised visual masking
von: Çoğalan, Uğur, et al.
Veröffentlicht: (2023)

Which images to label for few-shot medical landmark detection?
von: Quan, Quan, et al.
Veröffentlicht: (2021)

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

Single-image reflection removal via self-supervised diffusion models
von: Lu, Zhengyang, et al.
Veröffentlicht: (2024)

Leveraging pretrained RGB denoisers for hyperspectral image restoration
von: Picone, Daniele, et al.
Veröffentlicht: (2026)

MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention
von: Arora, Aadya, et al.
Veröffentlicht: (2025)

Topology-Driven Fusion of nnU-Net and MedNeXt for Accurate Brain Tumor Segmentation on Sub-Saharan Africa Dataset
von: Bohara, Prabin, et al.
Veröffentlicht: (2026)

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

A multi-stage semi-supervised learning for ankle fracture classification on CT images
von: Liu, Hongzhi, et al.
Veröffentlicht: (2024)

Designing robust diffractive neural networks with improved transverse shift tolerance
von: Soshnikov, Daniil V., et al.
Veröffentlicht: (2024)

Regularizing INR with diffusion prior self-supervised 3D reconstruction of neutron computed tomography data
von: Hossain, Maliha, et al.
Veröffentlicht: (2026)

Accelerated deep self-supervised ptycho-laminography for three-dimensional nanoscale imaging of integrated circuits
von: Kang, Iksung, et al.
Veröffentlicht: (2023)

Hyperspectral and multispectral image fusion with arbitrary resolution through self-supervised representations
von: Wang, Ting, et al.
Veröffentlicht: (2024)

DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation
von: Fu, Zhaojin, et al.
Veröffentlicht: (2024)

A self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging
von: Li, Peichao, et al.
Veröffentlicht: (2024)

Recursive classification of satellite imaging time-series: An application to land cover mapping
von: Calatrava, Helena, et al.
Veröffentlicht: (2023)

Experts' cognition-driven safe noisy labels learning for precise segmentation of residual tumor in breast cancer
von: Yang, Yongquan, et al.
Veröffentlicht: (2023)