Deep learning COVID-19 features on CXR using limited training data sets
Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-
ray (CXR) image for COVID-19 diagnosis and patient triage is becoming important …
ray (CXR) image for COVID-19 diagnosis and patient triage is becoming important …
Radiological cardiothoracic ratio in evidence-based medicine
K Truszkiewicz, R Poręba, P Gać - Journal of Clinical Medicine, 2021 - mdpi.com
The cardiothoracic ratio (CTR), expressing the relationship between the size of the heart and
the transverse dimension of the chest measured on a chest PA radiograph, is a commonly …
the transverse dimension of the chest measured on a chest PA radiograph, is a commonly …
Chest x-ray in emergency radiology: What artificial intelligence applications are available?
G Irmici, M Cè, E Caloro, N Khenkina, G Della Pepa… - Diagnostics, 2023 - mdpi.com
Due to its widespread availability, low cost, feasibility at the patient's bedside and
accessibility even in low-resource settings, chest X-ray is one of the most requested …
accessibility even in low-resource settings, chest X-ray is one of the most requested …
Unsupervised domain adaptation for automatic estimation of cardiothoracic ratio
The cardiothoracic ratio (CTR), a clinical metric of heart size in chest X-rays (CXRs), is a key
indicator of cardiomegaly. Manual measurement of CTR is time-consuming and can be …
indicator of cardiomegaly. Manual measurement of CTR is time-consuming and can be …
Learning deformable registration of medical images with anatomical constraints
Deformable image registration is a fundamental problem in the field of medical image
analysis. During the last years, we have witnessed the advent of deep learning-based image …
analysis. During the last years, we have witnessed the advent of deep learning-based image …
Imaging the adult with congenital heart disease: a multimodality imaging approach—position paper from the EACVI
G Di Salvo, O Miller, S Babu Narayan… - European Heart …, 2018 - academic.oup.com
Advances in the diagnosis and management of congenital heart disease have led to a
marked improvement in the survival of adult with congenital heart disease (ACHD) patients …
marked improvement in the survival of adult with congenital heart disease (ACHD) patients …
Explaining the black-box smoothly—a counterfactual approach
Abstract We propose a BlackBox Counterfactual Explainer, designed to explain image
classification models for medical applications. Classical approaches (eg,, saliency maps) …
classification models for medical applications. Classical approaches (eg,, saliency maps) …
[HTML][HTML] Deep learning-based pulmonary tuberculosis automated detection on chest radiography: large-scale independent testing
W Zhou, G Cheng, Z Zhang, L Zhu… - … Imaging in Medicine …, 2022 - ncbi.nlm.nih.gov
Background It is critical to have a deep learning-based system validated on an external
dataset before it is used to assist clinical prognoses. The aim of this study was to assess the …
dataset before it is used to assist clinical prognoses. The aim of this study was to assess the …
Automatic cardiothoracic ratio calculation with deep learning
Deep learning is a growing trend in medical image analysis. There are limited data of deep
learning techniques applied in Chest X-rays. This paper proposed a deep learning algorithm …
learning techniques applied in Chest X-rays. This paper proposed a deep learning algorithm …
Determinants of outpatient clinic attendance amongst adults with congenital heart disease and outcome
A Kempny, GP Diller, K Dimopoulos… - International Journal of …, 2016 - Elsevier
Background Adult congenital heart disease (ACHD) guidelines advise life-long, regular,
follow up in predefined intervals for ACHD patients. However, limited data exist to support …
follow up in predefined intervals for ACHD patients. However, limited data exist to support …