AIMC Topic: Solitary Pulmonary Nodule

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Artificial intelligence-based graded training of pulmonary nodules for junior radiology residents and medical imaging students.

BMC medical education Jul 9, 2024
BACKGROUND: To evaluate the efficiency of artificial intelligence (AI)-assisted diagnosis system in the pulmonary nodule detection and diagnosis training of junior radiology residents and medical imaging students.
Clinical Competence Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Female Students, Medical Male Radiology Internship and Residency Humans Artificial Intelligence
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A multiscale 3D network for lung nodule detection using flexible nodule modeling.

Medical physics Jul 1, 2024
BACKGROUND: Lung cancer is the most common type of cancer. Detection of lung cancer at an early stage can reduce mortality rates. Pulmonary nodules may represent early cancer and can be identified through computed tomography (CT) scans. Malignant ris...
Deep Learning Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule Humans Tomography, X-Ray Computed
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Artificial Intelligence: Can It Save Lives, Hospitals, and Lung Screening?

The Annals of thoracic surgery May 28, 2024
BACKGROUND: Early detection is essential in lung cancer survival. Lung screening or incidental detection on unrelated imaging holds the most promise for early detection. With the large volume of imaging performed today, management of incidental pulmo...
Early Detection of Cancer Incidental Findings Humans Artificial Intelligence Retrospective Studies Middle Aged Tomography, X-Ray Computed Female Lung Neoplasms Aged Mass Screening Male Solitary Pulmonary Nodule
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Value of CT-Based Deep Learning Model in Differentiating Benign and Malignant Solid Pulmonary Nodules ≤ 8 mm.

Academic radiology May 27, 2024
RATIONALE AND OBJECTIVES: We examined the effectiveness of computed tomography (CT)-based deep learning (DL) models in differentiating benign and malignant solid pulmonary nodules (SPNs) ≤ 8 mm.
Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Female Aged Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Adult Male Middle Aged
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Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.

Lung May 23, 2024
BACKGROUND: There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (C...
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Predictive Value of Tests Humans Tomography, X-Ray Computed Risk Assessment Diagnosis, Computer-Assisted Deep Learning Lung Neoplasms
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Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.

European radiology experimental May 20, 2024
BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR).
Pulmonary Emphysema Radiation Dosage Female Aged Sensitivity and Specificity Male Humans Artificial Intelligence Software Tomography, X-Ray Computed Middle Aged Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted
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Attention pyramid pooling network for artificial diagnosis on pulmonary nodules.

PloS one May 16, 2024
The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. Howev...
Multiple Pulmonary Nodules Tomography, X-Ray Computed Solitary Pulmonary Nodule Humans Lung Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Deep Learning Algorithms Lung Neoplasms
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Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

Cancer imaging : the official publication of the International Cancer Imaging Society May 9, 2024
BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduc...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Humans Phantoms, Imaging Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiation Dosage
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Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

Biomedical physics & engineering express May 8, 2024
. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by d...
Humans Neural Networks, Computer Algorithms Deep Learning China Reproducibility of Results Lung Neoplasms Aged Retrospective Studies Solitary Pulmonary Nodule Multiple Pulmonary Nodules Male Tomography, X-Ray Computed Early Detection of Cancer Middle Aged Female
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Clinical value of deep learning image reconstruction on the diagnosis of pulmonary nodule for ultra-low-dose chest CT imaging.

Clinical radiology Apr 20, 2024
PURPOSE: To compare the image quality and pulmonary nodule detectability between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in ultra-low-dose CT (ULD-CT).
Middle Aged Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Aged Humans Adult Prospective Studies Male Tomography, X-Ray Computed Solitary Pulmonary Nodule Female Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Signal-To-Noise Ratio
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