ArticleDistributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health : Third MICCAI Workshop, DeCaF 2022 and Second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Sin...2022
Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation.
Article in Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health : Third MICCAI Workshop, DeCaF 2022 and Second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Sin..., 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Catheter detection and segmentation in X-ray images via multi-task learning.International journal of computer assisted radiology and surgery · 2026Article
- Comparative analysis of supervised and self-supervised learning with small and imbalanced medical imaging datasets.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
- Exploration of CT-based discrimination and diagnosis of various pathological types of ground glass nodules in the lungs.BMC medical imaging · 2025Article
- A deep ensemble learning framework for glioma segmentation and grading prediction.Scientific reports · 2025Article
- A deep learning framework deploying segment anything to detect pan-cancer mitotic figures from haematoxylin and eosin-stained slides.Communications biology · 2024Article
- 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
- Article
- 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
- Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Cross-Attention for Improved Motion Correction in Brain PET.Machine learning in clinical neuroimaging : 6th international workshop, MLCN 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, proceedings. MLCN (Workshop) (6th : 2023 : Vancouver, B.C.) · 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
- Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation.Information processing in medical imaging : proceedings of the ... conference · 2023Article
- Article
- SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining.Medical image analysis · 2023Article
- Class-Aware Adversarial Transformers for Medical Image Segmentation.Advances in neural information processing systems · 2022Article
- Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Many medical datasets have recently been created for medical image segmentation tasks, and it is natural to question whether we can use them to sequentially train a single model that (1) performs better on all these datasets, and (2) generalizes well and transfers better to the unknown target site domain. Prior works have achieved this goal by jointly training one model on multi-site datasets, which achieve competitive performance on average but such methods rely on the assumption about the availability of all training data, thus limiting its effectiveness in practical deployment. In this paper, we propose a novel multi-site segmentation framework called
Indexed as
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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.