Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder

10/04/2018
by   Maayan Frid-Adar, et al.
0

Accurate segmentation of anatomical structures in chest radiographs is essential for many computer-aided diagnosis tasks. In this paper we investigate the latest fully-convolutional architectures for the task of multi-class segmentation of the lungs field, heart and clavicles in a chest radiograph. In addition, we explore the influence of using different loss functions in the training process of a neural network for semantic segmentation. We evaluate all models on a common benchmark of 247 X-ray images from the JSRT database and ground-truth segmentation masks from the SCR dataset. Our best performing architecture, is a modified U-Net that benefits from pre-trained encoder weights. This model outperformed the current state-of-the-art methods tested on the same benchmark, with Jaccard overlap scores of 96.1 for heart and 85.5

READ FULL TEXT

page 5

page 7

research
01/30/2017

Fully Convolutional Architectures for Multi-Class Segmentation in Chest Radiographs

The success of deep convolutional neural networks on image classificatio...
research
09/14/2020

EfficientSeg: An Efficient Semantic Segmentation Network

Deep neural network training without pre-trained weights and few data is...
research
06/10/2021

Anatomy X-Net: A Semi-Supervised Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification

Thoracic disease detection from chest radiographs using deep learning me...
research
03/20/2020

Bone Structures Extraction and Enhancement in Chest Radiographs via CNN Trained on Synthetic Data

In this paper, we present a deep learning-based image processing techniq...
research
06/11/2020

Automated Identification of Thoracic Pathology from Chest Radiographs with Enhanced Training Pipeline

Chest x-rays are the most common radiology studies for diagnosing lung a...
research
07/03/2021

VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays

We introduce a new benchmark dataset, namely VinDr-RibCXR, for automatic...

Please sign up or login with your details

Forgot password? Click here to reset