deep learning

Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning
Lung cancer screening (LCS) using annual computed tomography (CT) scanning significantly reduces mortality by detecting cancerous lung …
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Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning
Evaluation of automated airway morphological quantification for assessing fibrosing lung disease
Patients with lung damage by scarring typically have abnormally larger airways. This difference in airway size between patients and healthy individuals can be seen with 3D xrays, known as a CT scan. We present a new software program called AirQuant to measure all airways of a patient’s CT scan. We compare measurements between 14 healthy individuals and 14 diseased patients. We found that airway disease was worse in the lower lungs and furthermore their airways were also more twisted. Measurements used by AirQuant, has potential as new markers in imaging to help us understand how bad a patient’s disease is.
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Evaluation of automated airway morphological quantification for assessing fibrosing lung disease
Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors
During the COVID-19 pandemic, the sheer volume of imaging performed in an emergency setting for COVID-19 diagnosis has resulted in a …
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Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors
CenTime: Event-conditional modelling of censoring in survival analysis
Survival analysis is a valuable tool for estimating the time until specific events, such as death or cancer recurrence, based on …
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CenTime: Event-conditional modelling of censoring in survival analysis
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study
In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. …
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A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study
MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels
Semi-supervised learning (SSL) is a promising machine learning paradigm to address the ubiquitous issue of label scarcity in medical …
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Utilisation of deep learning for COVID-19 diagnosis
The COVID-19 pandemic that began in 2019 has resulted in millions of deaths worldwide. Over this period, the economic and healthcare …
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Utilisation of deep learning for COVID-19 diagnosis
Airway measurement by refinement of synthetic images improves mortality prediction in idiopathic pulmonary fibrosis
Several chronic lung diseases, like idiopathic pulmonary fibrosis (IPF) are characterised by abnormal dilatation of the airways. …
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Airway measurement by refinement of synthetic images improves mortality prediction in idiopathic pulmonary fibrosis
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation
This paper concerns pseudo labelling in segmentation. Our contribution is fourfold. Firstly, we present a new formulation of …
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Deep Learning Based Long Term Mortality Prediction in the National Lung Screening Trial
In this study, the long-term mortality in the National Lung Screening Trial (NLST) was investigated using a deep learning-based method. …
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Deep Learning Based Long Term Mortality Prediction in the National Lung Screening Trial