AIMC Topic: Bronchoscopy
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A machine learning texture model for classifying lung cancer subtypes using preliminary bronchoscopic findings.
Medical physics
Nov 8, 2018
PURPOSE: Bronchoscopy is useful in lung cancer detection, but cannot be used to differentiate cancer types. A computer-aided diagnosis (CAD) system was proposed to distinguish malignant cancer types to achieve objective diagnoses.
Defining lower airway bacterial infection in children with chronic endobronchial disorders.
Pediatric pulmonology
Dec 19, 2017
BACKGROUND: Differentiating lower airway bacterial infection from possible upper airway contamination in children with endobronchial disorders undergoing bronchoalveolar lavage (BAL) is important for guiding management. A diagnostic bacterial load th...
Deep monocular 3D reconstruction for assisted navigation in bronchoscopy.
International journal of computer assisted radiology and surgery
May 15, 2017
PURPOSE: In bronchoschopy, computer vision systems for navigation assistance are an attractive low-cost solution to guide the endoscopist to target peripheral lesions for biopsy and histological analysis. We propose a decoupled deep learning architec...
Surgery for predominant lesion in nonlocalized bronchiectasis.
The Journal of thoracic and cardiovascular surgery
Dec 15, 2016
OBJECTIVE: Patients with nonlocalized bronchiectasis are encountered commonly; however, there is little information regarding surgical intervention in this patient population. The aim of this study was to evaluate symptomatic response and safety of a...
Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume.
International journal of computer assisted radiology and surgery
Oct 28, 2016
PURPOSE: Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3...
[Application and progress of artificial intelligence technology in interventional pulmonology].
Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Jul 12, 2025
In recent years, interventional pulmonology has advanced rapidly, with bronchoscopy becoming a cornerstone in the diagnosis and treatment of respiratory diseases. The integration of artificial intelligence (AI) technology has established an intellige...
Artificial intelligence in bronchoscopy: a systematic review.
European respiratory review : an official journal of the European Respiratory Society
Apr 1, 2025
BACKGROUND: Artificial intelligence (AI) systems have been implemented to improve the diagnostic yield and operators' skills within endoscopy. Similar AI systems are now emerging in bronchoscopy. Our objective was to identify and describe AI systems ...
Artificial Intelligence Feedback for Bronchoscopy Training: Old Wine in a New Bottle or True Innovation?
Chest
Feb 1, 2024
Motivation and Learning: Leveraging Artificial Intelligence to Improve Bronchoscopy Performance.
Chest
Feb 1, 2024
[Recent advances in diagnosis of pulmonary nodule].
Zhonghua wai ke za zhi [Chinese journal of surgery]
May 1, 2022
With the popularization of health screening and the widespread use of low-dose computed tomography, the detection rate of lung nodules has increased year after year. However, the false positive rates testified by surgery of these lung nodules are sti...
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