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Solitary Pulmonary Nodule

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Development of a deep learning-based method to diagnose pulmonary ground-glass nodules by sequential computed tomography imaging.

Thoracic cancer
BACKGROUND: Early identification of the malignant propensity of pulmonary ground-glass nodules (GGNs) can relieve the pressure from tracking lesions and personalized treatment adaptation. The purpose of this study was to develop a deep learning-based...

Application of Deep Learning in Lung Cancer Imaging Diagnosis.

Journal of healthcare engineering
Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. It poses a great threat to human health and it mainly occurs in smokers. In our country, with the acceleration of industrialization, environmental pol...

Deep-learning reconstruction for ultra-low-dose lung CT: Volumetric measurement accuracy and reproducibility of artificial ground-glass nodules in a phantom study.

The British journal of radiology
OBJECTIVES: The lung nodule volume determined by CT is used for nodule diagnoses and monitoring tumor responses to therapy. Increased image noise on low-dose CT degrades the measurement accuracy of the lung nodule volume. We compared the volumetric a...

CAD system for lung nodule detection using deep learning with CNN.

Medical & biological engineering & computing
The early detection of pulmonary nodules using computer-aided diagnosis (CAD) systems is very essential in reducing mortality rates of lung cancer. In this paper, we propose a new deep learning approach to improve the classification accuracy of pulmo...

Identification of Benign and Malignant Lung Nodules in CT Images Based on Ensemble Learning Method.

Interdisciplinary sciences, computational life sciences
BACKGROUND AND OBJECTIVE: Under the background of urgent need for computer-aided technology to provide physicians with objective decision support, aiming at reducing the false positive rate of nodule CT detection in pulmonary nodules detection and im...

One deep learning local-global model based on CT imaging to differentiate between nodular cryptococcosis and lung cancer which are hard to be diagnosed.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVES: We aim to evaluate a deep learning (DL) model and radiomic model for preoperative differentiation of nodular cryptococcosis from solitary lung cancer in patients with malignant features on CT images.

A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning.

Computers in biology and medicine
Lung cancer has one of the highest mortalities of all cancers. According to the National Lung Screening Trial, patients who underwent low-dose computed tomography (CT) scanning once a year for 3 years showed a 20% decline in lung cancer mortality. To...