AIMC Topic: Bronchi

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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...

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...

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...

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...

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...

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...

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 ...

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...

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...

Two different methods of bronchial dissection and coverage in robotic bilobectomy for advanced lung cancer.

Asian journal of endoscopic surgery
INTRODUCTION: Due to its many technical advantages, the scope of robot-assisted thoracic surgery (RATS) is expanding to include extended pulmonary resection. Among such procedures, right bilobectomy is one with a high risk of inducing development of ...