# Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images

arXiv: https://arxiv.org/abs/2110.00682 · HTML: https://mlsanity.com/paper/2110.00682/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 12 references that are in the map.
- First posted on arXiv 1 Oct 2021.

## Builds on (most cited first, 2 of 2)

- [Studying Robustness of Semantic Segmentation under Domain Shift in cardiac MRI](https://mlsanity.com/paper/2011.07592/) (2020)
- [Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer](https://mlsanity.com/paper/2012.14785/) (2020)

## Built on by (most cited first, 4 of 4)

- [EchoONE: Segmenting Multiple echocardiography Planes in One Model](https://mlsanity.com/paper/2412.02993/) (2024)
- [How good nnU-Net for Segmenting Cardiac MRI: A Comprehensive Evaluation](https://mlsanity.com/paper/2408.06358/) (2024)
- [Compositional Segmentation of Cardiac Images Leveraging Metadata](https://mlsanity.com/paper/2410.23130/) (2024)
- [Multi-view Cardiac Image Segmentation via Trans-Dimensional Priors](https://mlsanity.com/paper/2404.16708/) (2024)

## Abstract (arXiv)

We proposed a multi-view SA-LA model for simultaneous segmentation of RV on the short-axis (SA) and long-axis (LA) cardiac MR images. The multi-view SA-LA model is a multi-encoder, multi-decoder U-Net architecture based on the U-Net model. One encoder-decoder pair segments the RV on SA images and the other pair on LA images. Multi-view SA-LA model assembles an extremely rich set of synergistic features, at the root of the encoder branch, by combining feature maps learned from matched SA and LA cardiac MR images. Segmentation performance is further enhanced by: (1) incorporating spatial context of LV as a prior and (2) performing deep supervision in the last three layers of the decoder branch. Multi-view SA-LA model was extensively evaluated on the MICCAI 2021 Multi- Disease, Multi-View, and Multi- Centre RV Segmentation Challenge dataset (M&Ms-2021). M&Ms-2021 dataset consists of multi-phase, multi-view cardiac MR images of 360 subjects acquired at four clinical centers with three different vendors. On the challenge cohort (160 subjects), the proposed multi-view SA-LA model achieved a Dice Score of 91% and Hausdorff distance of 11.2 mm on short-axis images and a Dice Score of 89.6% and Hausdorff distance of 8.1 mm on long-axis images. Moreover, multi-view SA-LA model exhibited strong generalization to unseen RV related pathologies including Dilated Right Ventricle (DSC: SA 91.41%, LA 89.63%) and Tricuspidal Regurgitation (DSC: SA 91.40%, LA 90.40%) with low variance (std_DSC: SA <5%, LA<6%).