Catheters are the second most common abnormal finding on radiographs. The position of
catheters must be assessed on all radiographs because serious complications can arise if …

Abstract Background and Objective Peripherally inserted central catheter (PICC) is a novel
drug delivery mode which has been widely used in clinical practice. However, long-term …

This study presents a model to effectively recognise image noise of different types and
levels: impulse, Gaussian, Speckle and Poisson noise, and a mixture of multiple types of the …

Catheters are commonly inserted life supporting devices. Because serious complications
can arise from malpositioned catheters, X-ray images are used to assess the position of a …

This paper proposes an improved stochastic second order learning algorithm for supervised
neural network training. The proposed algorithm, named bounded stochastic diagonal …

In this research, a novel customized deep learning model is proposed to detect Tuberculosis
(TB) from chest X‐rays (CXR). The model is utilized for three experimentations:(i) …

Accurate real-time catheter segmentation is an important pre-requisite for robot-assisted
endovascular intervention. Most of the existing learning-based methods for catheter …

We develop and evaluate a deep learning algorithm to classify multiple catheters on
neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was …

Portable chest radiographs (CXRs) are commonly used in the intensive care unit (ICU) to
detect subtle pathological changes. However, exposure settings or patient and apparatus …

Purpose To present an automated method for detecting endotracheal (ET) tubes and
marking their tips in portable chest radiography (CXR) for intensive care units (ICUs) …