GAN Based Medical Image Registration
Not on the map. Why?
Abstract (arXiv)
Conventional approaches to image registration consist of time consuming iterative methods. Most current deep learning (DL) based registration methods extract deep features to use in an iterative setting. We propose an end-to-end DL method for registering multimodal images. Our approach uses generative adversarial networks (GANs) that eliminates the need for time consuming iterative methods, and directly generates the registered image with the deformation field. Appropriate constraints in the GAN cost function produce accurately registered images in less than a second. Experiments demonstrate their accuracy for multimodal retinal and cardiac MR image registration.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 May 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 4; 2022: 5.
9 papers.
- 2021Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentationcited by 22
- 2021CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysiscited by 8
- 2021Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentationcited by 5
- 2022Unsupervised Domain Adaptation Using Feature Disentanglement And GCNs For Medical Image Classificationcited by 5
- 2022Medical image registration using unsupervised deep neural network: A scoping literature reviewcited by 5
- 2021Multimodal Generalized Zero Shot Learning for Gleason Grading using Self-Supervised Learningcited by 4
- 2022Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classificationcited by 2
- 2022Improved Super Resolution of MR Images Using CNNs and Vision Transformerscited by 1
- 2022Cyclic Generative Adversarial Networks With Congruent Image-Report Generation For Explainable Medical Image Analysiscited by 0
- 2022Cyclic Generative Adversarial Networks With Congruent Image-Report Generation For Explainable Medical Image Analysis16 Nov 2022
- 2022Medical image registration using unsupervised deep neural network: A scoping literature review3 Aug 2022
- 2022Improved Super Resolution of MR Images Using CNNs and Vision Transformers24 Jul 2022
- 2022Unsupervised Domain Adaptation Using Feature Disentanglement And GCNs For Medical Image Classification27 Jun 2022
- 2022Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification4 Apr 2022
- 2021Multimodal Generalized Zero Shot Learning for Gleason Grading using Self-Supervised Learning15 Nov 2021
- 2021Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentation1 Oct 2021
- 2021CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis15 Jun 2021
- 2021Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation13 Apr 2021