ArticleMedical image analysis2019
BIRNet: Brain image registration using dual-supervised fully convolutional networks.
Article in Medical image analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.
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
67 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Application and Development of Deep Learning in Radiotherapy: A Systematic Review.Technology in cancer research & treatmentPooled it
- Article
- Hybrid transformer and convolution iteratively optimized pyramid network for brain large deformation image registration.Scientific reports · 2025Article
- A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond.Medical image analysis · 2025Review
- Non-Rigid Cycle Consistent Bidirectional Network with Transformer for Unsupervised Deformable Functional Magnetic Resonance Imaging Registration.Brain sciences · 2025Article
- The Fusion of Robotics and Imaging: A Vision of the Future.Methodist DeBakey cardiovascular journal · 2025Review
- PViT-AIR: Puzzling vision transformer-based affine image registration for multi histopathology and faxitron images of breast tissue.Medical image analysis · 2025Article
- RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images.Journal of imaging informatics in medicine · 2024Article
- Stepwise Corrected Attention Registration Network for Preoperative and Follow-Up Magnetic Resonance Imaging of Glioma Patients.Bioengineering (Basel, Switzerland) · 2024Article
- Medical image registration and its application in retinal images: a review.Visual computing for industry, biomedicine, and art · 2024Review
- A robust and interpretable deep learning framework for multi-modal registration via keypoints.Medical image analysis · 2023Article
- Unsupervised deep learning registration model for multimodal brain images.Journal of applied clinical medical physics · 2023Article
- macJNet: weakly-supervised multimodal image deformable registration using joint learning framework and multi-sampling cascaded MIND.Biomedical engineering online · 2023Article
- Advances in TEE-Centric Intraprocedural Multimodal Image Guidance for Congenital and Structural Heart Disease.Diagnostics (Basel, Switzerland) · 2023Review
- 3D Biological/Biomedical Image Registration with enhanced Feature Extraction and Outlier Detection.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- An overview of artificial intelligence in medical physics and radiation oncology.Journal of the National Cancer Center · 2023Review
- Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review.Neurorehabilitation and neural repair · 2023Article
- The Successive Next Network as Augmented Regularization for Deformable Brain MR Image Registration.Sensors (Basel, Switzerland) · 2023Article
- 3D-MASNet: 3D mixed-scale asymmetric convolutional segmentation network for 6-month-old infant brain MR images.Human brain mapping · 2023Article
- A brain CT-based approach for predicting and analyzing stroke-associated pneumonia from intracerebral hemorrhage.Frontiers in neurology · 2023Article
7 more citing papers are in PubMed but not listed here.
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
In this paper, we propose a deep learning approach for image registration by predicting deformation from image appearance. Since obtaining ground-truth deformation fields for training can be challenging, we design a fully convolutional network that is subject to dual-guidance: (1) Ground-truth guidance using deformation fields obtained by an existing registration method; and (2) Image dissimilarity guidance using the difference between the images after registration. The latter guidance helps avoid overly relying on the supervision from the training deformation fields, which could be inaccurate. For effective training, we further improve the deep convolutional network with gap filling, hierarchical loss, and multi-source strategies. Experiments on a variety of datasets show promising registration accuracy and efficiency compared with state-of-the-art methods.
Indexed as
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What Socratic 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 Socratic graph.