# Unsupervised cross domain learning with applications to 7 layer segmentation of OCTs

arXiv: https://arxiv.org/abs/2111.14804 · HTML: https://mlsanity.com/paper/2111.14804/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 8 references that are in the map.
- First posted on arXiv 23 Nov 2021.

## Builds on (most cited first, 1 of 1)

- [Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation](https://mlsanity.com/paper/1806.00600/) (2018)

## Abstract (arXiv)

Unsupervised cross domain adaptation for OCT 7 layer segmentation and other medical applications where labeled training data is only available in a source domain and unavailable in the target domain. Our proposed method helps generalize of deep learning to many areas in the medical field where labeled training data are expensive and time consuming to acquire or where target domains are too novel to have had labelling.