Fibro-CoSANet: Pulmonary Fibrosis Prognosis Prediction using a Convolutional Self Attention Network [PDF]
, 2021 Idiopathic pulmonary fibrosis (IPF) is a restrictive interstitial lung disease that causes lung function decline by lung tissue scarring. Although lung function decline is assessed by the forced vital capacity (FVC), determining the accurate progression of IPF remains a challenge. To address this challenge, we proposed Fibro-CoSANet, a novel end-to-end
arxiv +1 more source
Multiscale modelling of reversed Potts shunt as a potential palliative treatment for suprasystemic idiopathic pulmonary artery hypertension in children [PDF]
Biomechanics and Modeling in Mechanobiology (2022), 2021 Reversed Potts shunt (PS) was suggested as palliation for patients with suprasystemic pulmonary arterial hypertension (PAH) and right ventricular (RV) failure. PS, however, can result in poorly understood mortality. Here, a patient-specific geometrical multiscale model of PAH physiology and PS is developed for a paediatric PAH patient with stent-based ...
arxiv +1 more source
Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data [PDF]
arXiv, 2022 Idiopathic Pulmonary Fibrosis (IPF) is an inexorably progressive fibrotic lung disease with a variable and unpredictable rate of progression. CT scans of the lungs inform clinical assessment of IPF patients and contain pertinent information related to disease progression.
arxiv
Airway measurement by refinement of synthetic images improves mortality prediction in idiopathic pulmonary fibrosis [PDF]
arXiv, 2022 Several chronic lung diseases, like idiopathic pulmonary fibrosis (IPF) are characterised by abnormal dilatation of the airways. Quantification of airway features on computed tomography (CT) can help characterise disease progression. Physics based airway measurement algorithms have been developed, but have met with limited success in part due to the ...
arxiv
Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection [PDF]
In Lecture Notes in Computer Science, vol 11861. (2019) Springer,
Cham, 2019 Numerous lung diseases, such as idiopathic pulmonary fibrosis (IPF), exhibit dilation of the airways. Accurate measurement of dilatation enables assessment of the progression of disease. Unfortunately the combination of image noise and airway bifurcations causes high variability in the profiles of cross-sectional areas, rendering the identification of ...
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Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention [PDF]
, 2021 Computed Tomography (CT) plays an important role in monitoring radiation-induced Pulmonary Fibrosis (PF), where accurate segmentation of the PF lesions is highly desired for diagnosis and treatment follow-up. However, the task is challenged by ambiguous boundary, irregular shape, various position and size of the lesions, as well as the difficulty in ...
arxiv +1 more source
Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT Images [PDF]
arXiv, 2021 Pulmonary fibrosis is a devastating chronic lung disease that causes irreparable lung tissue scarring and damage, resulting in progressive loss in lung capacity and has no known cure. A critical step in the treatment and management of pulmonary fibrosis is the assessment of lung function decline, with computed tomography (CT) imaging being a ...
arxiv
Margin-Aware Intra-Class Novelty Identification for Medical Images [PDF]
Journal of Medical Imaging 2022, 2021 Traditional anomaly detection methods focus on detecting inter-class variations while medical image novelty identification is inherently an intra-class detection problem. For example, a machine learning model trained with normal chest X-ray and common lung abnormalities, is expected to discover and flag idiopathic pulmonary fibrosis which a rare lung ...
arxiv
Characterizing Pulmonary Fibrosis Patterns in Post-COVID-19 Patients through Machine Learning Algorithms [PDF]
arXiv, 2023 The COVID-19 pandemic has left a lasting impact on global healthcare systems, with increasing evidence of pulmonary fibrosis emerging as a post-infection complication. This study presents a comprehensive analysis of pulmonary fibrosis patterns in post-COVID-19 patients from South and Central Iraq, employing advanced machine learning algorithms.
arxiv
Evaluation of automated airway morphological quantification for assessing fibrosing lung disease [PDF]
arXiv, 2021 Abnormal airway dilatation, termed traction bronchiectasis, is a typical feature of idiopathic pulmonary fibrosis (IPF). Volumetric computed tomography (CT) imaging captures the loss of normal airway tapering in IPF. We postulated that automated quantification of airway abnormalities could provide estimates of IPF disease extent and severity.
arxiv