Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective

S Huang, J Yang, N Shen, Q Xu, Q Zhao - Seminars in Cancer Biology, 2023 - Elsevier
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the
world. The overall five-year survival rate of lung cancer is relatively lower than many leading …

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

D Ardila, AP Kiraly, S Bharadwaj, B Choi, JJ Reicher… - Nature medicine, 2019 - nature.com
With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer
death in the United States. Lung cancer screening using low-dose computed tomography …

Lung nodule and cancer detection in computed tomography screening

GD Rubin - Journal of thoracic imaging, 2015 - journals.lww.com
Fundamental to the diagnosis of lung cancer in computed tomography (CT) scans is the
detection and interpretation of lung nodules. As the capabilities of CT scanners have …

The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans

SG Armato III, G McLennan, L Bidaut… - Medical …, 2011 - Wiley Online Library
Purpose: The development of computer‐aided diagnostic (CAD) methods for lung nodule
detection, classification, and quantitative assessment can be facilitated through a well …

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis

W Sun, B Zheng, W Qian - Computers in biology and medicine, 2017 - Elsevier
This study aimed to analyze the ability of extracting automatically generated features using
deep structured algorithms in lung nodule CT image diagnosis, and compare its …

A new computationally efficient CAD system for pulmonary nodule detection in CT imagery

T Messay, RC Hardie, SK Rogers - Medical image analysis, 2010 - Elsevier
Early detection of lung nodules is extremely important for the diagnosis and clinical
management of lung cancer. In this paper, a novel computer aided detection (CAD) system …

On the performance of lung nodule detection, segmentation and classification

D Gu, G Liu, Z Xue - Computerized Medical Imaging and Graphics, 2021 - Elsevier
Computed tomography (CT) screening is an effective way for early detection of lung cancer
in order to improve the survival rate of such a deadly disease. For more than two decades …

Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: the ANODE09 study

B Van Ginneken, SG Armato III, B de Hoop… - Medical image …, 2010 - Elsevier
Numerous publications and commercial systems are available that deal with automatic
detection of pulmonary nodules in thoracic computed tomography scans, but a comparative …

Building a reference multimedia database for interstitial lung diseases

A Depeursinge, A Vargas, A Platon… - … medical imaging and …, 2012 - Elsevier
This paper describes the methodology used to create a multimedia collection of cases with
interstitial lung diseases (ILDs) at the University Hospitals of Geneva. The dataset contains …

A novel computer‐aided lung nodule detection system for CT images

M Tan, R Deklerck, B Jansen, M Bister… - Medical …, 2011 - Wiley Online Library
Purpose: The paper presents a complete computer‐aided detection (CAD) system for the
detection of lung nodules in computed tomography images. A new mixedfeature selection …