Automatic catheter detection in pediatric X-ray images using a scale-recurrent network and synthetic data

Abstract

Catheters are commonly inserted life supporting devices. X-ray images are used to assess the position of a catheter immediately after placement as serious complications can arise from malpositioned catheters. Previous computer vision approaches to detect catheters on X-ray images either relied on low-level cues that are not sufficiently robust or only capable of processing a limited number or type of catheters. With the resurgence of deep learning, supervised training approaches are begining to showing promising results. However, dense annotation maps are required, and the work of a human annotator is hard to scale. In this work, we proposed a simple way of synthesizing catheters on X-ray images and a scale recurrent network for catheter detection. By training on adult chest X-rays, the proposed network exhibits promising detection results on pediatric chest/abdomen X-rays in terms of both precision and recall.

arXiv commentaccepted to the 1st Conference on Medical Imaging with Deep Learning (MIDL2018), Amsterdam, The Netherlands

References in corpus (6)

• Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
• Fully Convolutional Networks for Semantic Segmentation
• Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification
• Sharpness-aware Low dose CT denoising using conditional generative adversarial network
• SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays
• Scale-recurrent Network for Deep Image Deblurring

Cited by in corpus (6)

• Deep Learning for Chest X-ray Analysis: A Survey
• Computer-Aided Assessment of Catheters and Tubes on Radiographs: How Good is Artificial Intelligence for Assessment?
• Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging
• Automatic classification of multiple catheters in neonatal radiographs with deep learning
• End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Intervention
• A Research Agenda on Pediatric Chest X-Ray: Is Deep Learning Still in Childhood?