ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2022
Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation.
Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
28 citing papers in PubMed.
- A fused attention-based hybrid model for semi-supervised medical image segmentation.Biomedical engineering advances · 2026Article
- ProtoSAM for automated one shot medical image segmentation using foundational models.Scientific reports · 2025Article
- FFTMed: leveraging fast-fourier transform for a lightweight and adversarial-resilient medical image segmentation framework.Scientific reports · 2025Article
- A highly generalized federated learning algorithm for brain tumor segmentation.Scientific reports · 2025Article
- Improved SwinUNet with fusion transformer and large kernel convolutional attention for liver and tumor segmentation in CT images.Scientific reports · 2025Article
- Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study.BMC medical imaging · 2025Article
- A deep ensemble learning framework for glioma segmentation and grading prediction.Scientific reports · 2025Article
- Enhanced Cross-stage-attention U-Net for esophageal target volume segmentation.BMC medical imaging · 2024Article
- Robust thoracic CT image registration with environmental adaptability using dynamic Welsch's function and hierarchical structure-awareness strategy.Quantitative imaging in medicine and surgery · 2024Article
- Multi-scale input layers and dense decoder aggregation network for COVID-19 lesion segmentation from CT scans.Scientific reports · 2024Article
- Article
- Mine Your Own Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels.IEEE transactions on pattern analysis and machine intelligence · 2024Article
- Next-Gen Medical Imaging: U-Net Evolution and the Rise of Transformers.Sensors (Basel, Switzerland) · 2024Review
- Enhancing automatic prediction of clinically significant prostate cancer with deep transfer learning 2.5-dimensional segmentation on bi-parametric magnetic resonance imaging (bp-MRI).Quantitative imaging in medicine and surgery · 2024Article
- Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective.Advances in neural information processing systems · 2023Article
- Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Improve the performance of CT-based pneumonia classification via source data reweighting.Scientific reports · 2023Article
- Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation.Information processing in medical imaging : proceedings of the ... conference · 2023Article
- Dense regression activation maps for lesion segmentation in CT scans of COVID-19 patients.Medical image analysis · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Contrastive learning (CL) aims to learn useful representation without relying on expert annotations in the context of medical image segmentation. Existing approaches mainly contrast a single positive vector (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.