# Automated Cardiothoracic Ratio Calculation and Cardiomegaly Detection using Deep Learning Approach

arXiv: https://arxiv.org/abs/2002.07468 · HTML: https://mlsanity.com/paper/2002.07468/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Feb 2020.

## Built on by (most cited first, 3 of 3)

- [Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted Diagnosis of Cardiomegaly](https://mlsanity.com/paper/2101.07606/) (2021)
- [Explaining the Black-box Smoothly- A Counterfactual Approach](https://mlsanity.com/paper/2101.04230/) (2021)
- [X-Ragent: Tool-Augmented Reinforcement Learning for Evidence-Grounded Chest X-Ray Reasoning](https://mlsanity.com/paper/2610.16811/) (2026)

## Abstract (arXiv)

We propose an algorithm for calculating the cardiothoracic ratio (CTR) from chest X-ray films. Our approach applies a deep learning model based on U-Net with VGG16 encoder to extract lung and heart masks from chest X-ray images and calculate CTR from the extents of obtained masks. Human radiologists evaluated our CTR measurements, and 76.5% were accepted to be included in medical reports without any need for adjustment. This result translates to a large amount of time and labor saved for radiologists using our automated tools.