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Bronchi

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Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.

Nature communications
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative planning. Despite the promise of 3D reconstruction, clinical adoption remains limited due to time c...

Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study.

Radiology
Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent...

TNN: Tree Neural Network for Airway Anatomical Labeling.

IEEE transactions on medical imaging
Detailed anatomical labeling of bronchial trees extracted from CT images can be used as fine-grained maps for intra-operative navigation. To cater to the sparse distribution of airway voxels and large class imbalance in 3D image space, a graph-neural...

Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction.

European radiology
OBJECTIVES: Computed tomography (CT)-based bronchial parameters correlate with disease status. Segmentation and measurement of the bronchial lumen and walls usually require significant manpower. We evaluate the reproducibility of a deep learning and ...

Systematic Bronchoscopy: the Four Landmarks Approach.

Journal of visualized experiments : JoVE
Flexible bronchoscopy is a technically difficult procedure and has been identified as the most important procedure that should be integrated into a simulation-based training program for pulmonologists. However, more specific guidelines that govern br...

Console and bedside surgeon fused robot-assisted thoracic surgery.

General thoracic and cardiovascular surgery
In the last decade, even thoracic surgery has seen an increase in the use of robotic surgical systems, and robot-assisted thoracic surgery (RATS) is considered one of the main issues. While RATS is associated with solo manipulative freedom and high-d...

Artificial Intelligence Improves Novices' Bronchoscopy Performance: A Randomized Controlled Trial in a Simulated Setting.

Chest
BACKGROUND: Navigating through the bronchial tree and visualizing all bronchial segments is the initial step toward learning flexible bronchoscopy. A novel bronchial segment identification system based on artificial intelligence (AI) has been develop...

Artificial intelligence-assisted quantitative CT analysis of airway changes following SABR for central lung tumors.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
INTRODUCTION: Use of stereotactic ablative radiotherapy (SABR) for central lung tumors can result in up to a 35% incidence of late pulmonary toxicity. We evaluated an automated scoring method to quantify post-SABR bronchial changes by using artificia...

Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.

Respiratory research
BACKGROUND: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI...

BCNet: Bronchus Classification via Structure Guided Representation Learning.

IEEE transactions on medical imaging
CT-based bronchial tree analysis is a key step for the diagnosis of lung and airway diseases. However, the topology of bronchial trees varies across individuals, which presents a challenge to the automatic bronchus classification. To solve this issue...