AIMC Topic: Lung

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Twenty-Four Years' Experience With a Pulmonary Pathology Journal Club: What Have We Learned?

Archives of pathology & laboratory medicine
CONTEXT.—: A monthly pathology journal club has met for 24 years. It was established to help members stay apprised of the literature relevant to diagnostic pulmonary pathology.

Single Inspiratory Chest CT-based Generative Deep Learning Models to Evaluate Functional Small Airways Disease.

Radiology. Artificial intelligence
Purpose To develop a deep learning model that uses a single inspiratory chest CT scan to perform parametric response mapping (PRM) and predict functional small airways disease (fSAD). Materials and Methods In this retrospective study, predictive and ...

Quantitative computed tomography imaging classification of cement dust-exposed patients-based Kolmogorov-Arnold networks.

Artificial intelligence in medicine
BACKGROUND: Occupational health assessment is critical for detecting respiratory issues caused by harmful exposures, such as cement dust. Quantitative computed tomography (QCT) imaging provides detailed insights into lung structure and function, enha...

Quantitative Computed Tomography Measures of Lung Fibrosis and Outcomes in the National Lung Screening Trial.

Annals of the American Thoracic Society
Incidental features of interstitial lung disease (ILD) are commonly observed on chest computed tomography (CT) scans and are independently associated with poor outcomes. Although most studies to date have relied on qualitative assessments of ILD, qu...

A multi-stage 3D convolutional neural network algorithm for CT-based lung segment parcellation.

Journal of applied clinical medical physics
BACKGROUND: Current approaches to lung parcellation utilize established fissures between lobes to provide estimates of lobar volume. However, deep learning segment parcellation provides the ability to better assess regional heterogeneity in ventilati...

Application of Quantitative CT and Machine Learning in the Evaluation and Diagnosis of Polymyositis/Dermatomyositis-Associated Interstitial Lung Disease.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate lung changes in patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) using quantitative CT and to construct a diagnostic model to evaluate the application of quantitative...

Application of a pulmonary nodule detection program using AI technology to ultra-low-dose CT: differences in detection ability among various image reconstruction methods.

Japanese journal of radiology
PURPOSE: This study aimed to investigate the performance of an artificial intelligence (AI)-based lung nodule detection program in ultra-low-dose CT (ULDCT) imaging, with a focus on the influence of various image reconstruction methods on detection a...

Current State of Fibrotic Interstitial Lung Disease Imaging.

Radiology
Interstitial lung disease (ILD) diagnosis is complex, continuously evolving, and increasingly reliant on thin-section chest CT. Multidisciplinary discussion aided by a thorough radiologic review can achieve a high-confidence diagnosis of ILD in the m...

Deep Learning Models for CT Segmentation of Invasive Pulmonary Aspergillosis, Mucormycosis, Bacterial Pneumonia and Tuberculosis: A Multicentre Study.

Mycoses
BACKGROUND: The differential diagnosis of invasive pulmonary aspergillosis (IPA), pulmonary mucormycosis (PM), bacterial pneumonia (BP) and pulmonary tuberculosis (PTB) are challenging due to overlapping clinical and imaging features. Manual CT lesio...