mlsanityData to 14 Oct 2026

Training Data Independent Image Registration With GANs Using Transfer Learning And Segmentation Information

arXiv 1903.10139 ↗First posted 25 Mar 2019cs.CVcited by 8

Not on the map. Why?

Abstract (arXiv)

Registration is an important task in automated medical image analysis. Although deep learning (DL) based image registration methods out perform time consuming conventional approaches, they are heavily dependent on training data and do not generalize well for new images types. We present a DL based approach that can register an image pair which is different from the training images. This is achieved by training generative adversarial networks (GANs) in combination with segmentation information and transfer learning. Experiments on chest Xray and brain MR images show that our method gives better registration performance over conventional methods.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Mar 2019.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 4.

8 papers.