Blunt thoracic trauma: role of chest radiography and comparison with CT—findings and literature review

K Polireddy, C Hoff, NP Kinger, A Tran, K Maddu - Emergency Radiology, 2022 - Springer
… and life-threatening pathologies and guiding further … chest radiographic findings associated
with various injuries resulting from blunt chest trauma and compares the efficacy of the chest

Development and validation of a deep learning–based automated detection algorithm for major thoracic diseases on chest radiographs

EJ Hwang, S Park, KN Jin, J Im Kim, SY Choi… - JAMA network …, 2019 - jamanetwork.com
… We defined the target diseases of our DLAD as major thoracic diseases that are common,
clinically important, and detectable on CRs. Specifically, we included pulmonary malignant …

Chest radiography in thoracic polytrauma

ML Ho, FR Gutierrez - American Journal of Roentgenology, 2009 - Am Roentgen Ray Soc
chest radiography in the evaluation of thoracic polytrauma. The pathophysiology, imaging
manifestations, and management recommendations for injuries to the chest … lung disease and …

Multiple feature integration for classification of thoracic disease in chest radiography

TK Khanh Ho, J Gwak - Applied Sciences, 2019 - mdpi.com
Featured Application We present handcrafted and deep feature integration approaches to
tackle the unified weakly-supervised 14-label chest X-ray image classification and …

Boosted cascaded convnets for multilabel classification of thoracic diseases in chest radiographs

P Kumar, M Grewal, MM Srivastava - … , Póvoa de Varzim, Portugal, June 27 …, 2018 - Springer
… for diagnosis of multiple diseases. With the availability of ChestX-ray14, which is a
massive dataset of chest X-ray images and provides annotations for 14 thoracic diseases; it is …

The added effect of artificial intelligence on physicians' performance in detecting thoracic pathologies on CT and chest X-ray: A systematic review

D Li, LM Pehrson, CA Lauridsen, L Tøttrup, M Fraccaro… - Diagnostics, 2021 - mdpi.com
… on human observers when diagnosing and/or detecting thoracic pathologies using different
diagnostic imaging modalities, such as chest X-ray and CT. Peer-reviewed, original research …

Thorax-net: an attention regularized deep neural network for classification of thoracic diseases on chest radiography

H Wang, H Jia, L Lu, Y Xia - IEEE journal of biomedical and …, 2019 - ieeexplore.ieee.org
… and more accessible diagnosis of thorax diseases on chest radiographs. However, due to
… neural network called Thorax-Net to diagnose 14 thorax diseases using chest radiography. …

Triple attention learning for classification of 14 thoracic diseases using chest radiography

H Wang, S Wang, Z Qin, Y Zhang, R Li, Y Xia - Medical Image Analysis, 2021 - Elsevier
… To adapt DenseNet-121 to our problem of classifying chest radiographs into C categories
of thoracic diseases, we keep only C neurons in its last FC layer, replace their activation with …

PediCXR: an open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children

HH Pham, NH Nguyen, TT Tran, TNM Nguyen… - Scientific Data, 2023 - nature.com
thoracic diseases cause several hundred thousand deaths every year among children under
five years old 1,2 . The chest radiograph … for common thoracic diseases in children such as …

Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

X Wang, Y Peng, L Lu, Z Lu… - Proceedings of the …, 2017 - openaccess.thecvf.com
… ing a hospital-scale chest X-ray image database, namely “ChestX-ray8”, mined from our
institute’s PACS system. First, we short-list eight common thoracic pathology keywords that are …