AIMC Topic: Solitary Pulmonary Nodule
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.
European radiology experimental
Nov 20, 2024
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).
Prediction of benign and malignant pulmonary nodules using preoperative CT features: using PNI-GARS as a predictor.
Frontiers in immunology
Nov 20, 2024
PURPOSE: The aim of this study was to develop and validate a prediction model for classification of pulmonary nodules based on preoperative CT imaging.
A novel benign and malignant classification model for lung nodules based on multi-scale interleaved fusion integrated network.
Scientific reports
Nov 11, 2024
One of the precursors of lung cancer is the presence of lung nodules, and accurate identification of their benign or malignant nature is important for the long-term survival of patients. With the development of artificial intelligence, deep learning ...
Lung nodule classification using radiomics model trained on degraded SDCT images.
Computer methods and programs in biomedicine
Oct 23, 2024
BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) screening has shown promise in reducing lung cancer mortality; however, it suffers from high false positive rates and a scarcity of available annotated datasets. To overcome these challeng...
An anthropomorphic diagnosis system of pulmonary nodules using weak annotation-based deep learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Oct 10, 2024
The accurate categorization of lung nodules in CT scans is an essential aspect in the prompt detection and diagnosis of lung cancer. The categorization of grade and texture for nodules is particularly significant since it can aid radiologists and cli...
Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.
Scientific reports
Sep 28, 2024
The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improv...
GC-WIR : 3D global coordinate attention wide inverted ResNet network for pulmonary nodules classification.
BMC pulmonary medicine
Sep 20, 2024
PURPOSE: Currently, deep learning methods for the classification of benign and malignant lung nodules encounter challenges encompassing intricate and unstable algorithmic models, limited data adaptability, and an abundance of model parameters.To tack...
Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules.
Annals of medicine
Sep 19, 2024
INTRODUCTION: Artificial intelligence (AI) shows promise for evaluating solitary pulmonary nodules (SPNs) on computed tomography (CT). Accurately determining cancer invasiveness can guide treatment. We aimed to investigate quantitative CT parameters ...
Pulmonary nodule visualization and evaluation of AI-based detection at various ultra-low-dose levels using photon-counting detector CT.
Acta radiologica (Stockholm, Sweden : 1987)
Sep 15, 2024
BACKGROUND: Radiation dose should be as low as reasonably achievable. With the invention of photon-counting detector computed tomography (PCD-CT), the radiation dose may be considerably reduced.
Combining Multistaged Filters and Modified Segmentation Network for Improving Lung Nodules Classification.
IEEE journal of biomedical and health informatics
Sep 5, 2024
Advancements in computational technology have led to a shift towards automated detection processes in lung cancer screening, particularly through nodule segmentation techniques. These techniques employ thresholding to distinguish between soft and fir...
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