A review on lung boundary detection in chest X-rays
S Candemir, S Antani - … journal of computer assisted radiology and …, 2019 - Springer
Purpose Chest radiography is the most common imaging modality for pulmonary diseases.
Due to its wide usage, there is a rich literature addressing automated detection of …
Due to its wide usage, there is a rich literature addressing automated detection of …
Computer‐aided diagnosis systems for lung cancer: challenges and methodologies
A El-Baz, GM Beache, G Gimel′ farb… - … journal of biomedical …, 2013 - Wiley Online Library
This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided …
oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided …
Automatic tuberculosis screening using chest radiographs
Tuberculosis is a major health threat in many regions of the world. Opportunistic infections in
immunocompromised HIV/AIDS patients and multi-drug-resistant bacterial strains have …
immunocompromised HIV/AIDS patients and multi-drug-resistant bacterial strains have …
Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration
The National Library of Medicine (NLM) is developing a digital chest X-ray (CXR) screening
system for deployment in resource constrained communities and developing countries …
system for deployment in resource constrained communities and developing countries …
Segmentation and classification on chest radiography: a systematic survey
T Agrawal, P Choudhary - The Visual Computer, 2023 - Springer
Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders.
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
Scan: Structure correcting adversarial network for organ segmentation in chest x-rays
Chest X-ray (CXR) is one of the most commonly prescribed medical imaging procedures,
often with over 2–10x more scans than other imaging modalities. These voluminous CXR …
often with over 2–10x more scans than other imaging modalities. These voluminous CXR …
ResBCDU-Net: a deep learning framework for lung CT image segmentation
Lung CT image segmentation is a key process in many applications such as lung cancer
detection. It is considered a challenging problem due to existing similar image densities in …
detection. It is considered a challenging problem due to existing similar image densities in …
Automated chest X-ray screening: Can lung region symmetry help detect pulmonary abnormalities?
KC Santosh, S Antani - IEEE transactions on medical imaging, 2017 - ieeexplore.ieee.org
Our primary motivator is the need for screening HIV+ populations in resource-constrained
regions for exposure to Tuberculosis, using posteroanterior chest radiographs (CXRs). The …
regions for exposure to Tuberculosis, using posteroanterior chest radiographs (CXRs). The …
Towards robust and effective shape modeling: Sparse shape composition
Organ shape plays an important role in various clinical practices, eg, diagnosis, surgical
planning and treatment evaluation. It is usually derived from low level appearance cues in …
planning and treatment evaluation. It is usually derived from low level appearance cues in …
Pneumonia detection on chest x-ray using machine learning paradigm
TB Chandra, K Verma - Proceedings of 3rd International Conference on …, 2020 - Springer
The chest radiograph is the globally accepted standard used for analysis of pulmonary
diseases. This paper presents a method for automatic detection of pneumonia on …
diseases. This paper presents a method for automatic detection of pneumonia on …