# Conditional Deformable Image Registration with Convolutional Neural Network

arXiv: https://arxiv.org/abs/2106.12673 · HTML: https://mlsanity.com/paper/2106.12673/

## Key facts

- Cited by 59 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 33 references that are in the map.
- First posted on arXiv 23 Jun 2021.

## Builds on (most cited first, 18 of 18)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization](https://mlsanity.com/paper/1703.06868/) (2017)
- [Identity Mappings in Deep Residual Networks](https://mlsanity.com/paper/1603.05027/) (2016)
- [HyperNetworks](https://mlsanity.com/paper/1609.09106/) (2016)
- [StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks](https://mlsanity.com/paper/1612.03242/) (2016)
- [A Learned Representation For Artistic Style](https://mlsanity.com/paper/1610.07629/) (2016)
- [StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks](https://mlsanity.com/paper/1710.10916/) (2017)
- [An Unsupervised Learning Model for Deformable Medical Image Registration](https://mlsanity.com/paper/1802.02604/) (2018)
- [Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks](https://mlsanity.com/paper/2006.16148/) (2020)
- [Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration](https://mlsanity.com/paper/1805.04605/) (2018)
- [Quicksilver: Fast Predictive Image Registration - a Deep Learning Approach](https://mlsanity.com/paper/1703.10908/) (2017)
- [Fast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks](https://mlsanity.com/paper/2003.09514/) (2020)
- [HyperMorph: Amortized Hyperparameter Learning for Image Registration](https://mlsanity.com/paper/2101.01035/) (2021)
- [End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network](https://mlsanity.com/paper/1704.06065/) (2017)
- [On Self Modulation for Generative Adversarial Networks](https://mlsanity.com/paper/1810.01365/) (2018)
- [mlVIRNET: Multilevel Variational Image Registration Network](https://mlsanity.com/paper/1909.10084/) (2019)

## Built on by (most cited first, 30 of 59)

- [Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning](https://mlsanity.com/paper/2112.04489/) (2021)
- [A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyond](https://mlsanity.com/paper/2307.15615/) (2023)
- [Large-Scale 3D Medical Image Pre-training with Geometric Context Priors](https://mlsanity.com/paper/2410.09890/) (2024)
- [Affine Medical Image Registration with Coarse-to-Fine Vision Transformer](https://mlsanity.com/paper/2203.15216/) (2022)
- [Learning the Effect of Registration Hyperparameters with HyperMorph](https://mlsanity.com/paper/2203.16680/) (2022)
- [The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients](https://mlsanity.com/paper/2112.06979/) (2021)
- [NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration](https://mlsanity.com/paper/2108.03443/) (2021)
- [A Robust and Interpretable Deep Learning Framework for Multi-modal Registration via Keypoints](https://mlsanity.com/paper/2304.09941/) (2023)
- [Deep Learning in Medical Image Registration: Magic or Mirage?](https://mlsanity.com/paper/2408.05839/) (2024)
- [Diffeomorphic Image Registration with Neural Velocity Field](https://mlsanity.com/paper/2202.12498/) (2022)
- [Voxelmorph++ Going beyond the cranial vault with keypoint supervision and multi-channel instance optimisation](https://mlsanity.com/paper/2203.00046/) (2022)
- [Medical Image Registration via Neural Fields](https://mlsanity.com/paper/2206.03111/) (2022)
- [Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-Recurrence Brain Tumor MRI Scans](https://mlsanity.com/paper/2206.03900/) (2022)
- [Learning-based and unrolled motion-compensated reconstruction for cardiac MR CINE imaging](https://mlsanity.com/paper/2209.03671/) (2022)
- [Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration](https://mlsanity.com/paper/2107.02433/) (2021)
- [ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration](https://mlsanity.com/paper/2206.13434/) (2022)
- [Robust Image Registration with Absent Correspondences in Pre-operative and Follow-up Brain MRI Scans of Diffuse Glioma Patients](https://mlsanity.com/paper/2210.11045/) (2022)
- [Deformable Cross-Attention Transformer for Medical Image Registration](https://mlsanity.com/paper/2303.06179/) (2023)
- [Adaptive Correspondence Scoring for Unsupervised Medical Image Registration](https://mlsanity.com/paper/2312.00837/) (2023)
- [SITReg: Multi-resolution architecture for symmetric, inverse consistent, and topology preserving image registration](https://mlsanity.com/paper/2303.10211/) (2023)
- [Weakly-supervised Biomechanically-constrained CT/MRI Registration of the Spine](https://mlsanity.com/paper/2205.07568/) (2022)
- [HyperSpace: Hypernetworks for spacing-adaptive image segmentation](https://mlsanity.com/paper/2407.03681/) (2024)
- [Adapting the Mean Teacher for keypoint-based lung registration under geometric domain shifts](https://mlsanity.com/paper/2207.00371/) (2022)
- [Conditional Deformable Image Registration with Spatially-Variant and Adaptive Regularization](https://mlsanity.com/paper/2303.10700/) (2023)
- [GSMorph: Gradient Surgery for cine-MRI Cardiac Deformable Registration](https://mlsanity.com/paper/2306.14687/) (2023)
- [Deep Implicit Optimization enables Robust Learnable Features for Deformable Image Registration](https://mlsanity.com/paper/2406.07361/) (2024)
- [Multi-scale Super-resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness](https://mlsanity.com/paper/2206.08984/) (2022)
- [Learning Physics-Inspired Regularization for Medical Image Registration with Hypernetworks](https://mlsanity.com/paper/2311.08239/) (2023)
- [Attention-aware non-rigid image registration for accelerated MR imaging](https://mlsanity.com/paper/2404.17621/) (2024)
- [UTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration](https://mlsanity.com/paper/2410.20348/) (2024)

## Abstract (arXiv)

Recent deep learning-based methods have shown promising results and runtime advantages in deformable image registration. However, analyzing the effects of hyperparameters and searching for optimal regularization parameters prove to be too prohibitive in deep learning-based methods. This is because it involves training a substantial number of separate models with distinct hyperparameter values. In this paper, we propose a conditional image registration method and a new self-supervised learning paradigm for deep deformable image registration. By learning the conditional features that are correlated with the regularization hyperparameter, we demonstrate that optimal solutions with arbitrary hyperparameters can be captured by a single deep convolutional neural network. In addition, the smoothness of the resulting deformation field can be manipulated with arbitrary strength of smoothness regularization during inference. Extensive experiments on a large-scale brain MRI dataset show that our proposed method enables the precise control of the smoothness of the deformation field without sacrificing the runtime advantage or registration accuracy.