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Related Concept Videos

Endoscopic Studies I: Bronchoscopy and Thoracoscopy01:30

Endoscopic Studies I: Bronchoscopy and Thoracoscopy

186
Endoscopy is a non-surgical medical technique used to examine a person's internal organs and vessels. This lesson will focus on two types of endoscopic studies: bronchoscopy and thoracoscopy.
Bronchoscopy
Description
Bronchoscopy is a procedure that involves direct visualization of the larynx, trachea, and bronchi for diagnostic and therapeutic purposes. A flexible fiber optic or rigid bronchoscope is used to carry out the procedure. The fiber-optic bronchoscope is more frequently used due...
186
Endoscopic Studies II: Thoracocentesis01:26

Endoscopic Studies II: Thoracocentesis

240
Thoracentesis(Thoracocentesis), commonly known as pleural tap, is a medical procedure where a 22 gauge needle is inserted into the pleural space, the area between the lung and chest wall. This procedure is commonly performed to diagnose or treat various respiratory disorders.
Description
Excess pleural fluid or air may accumulate in some respiratory disorders in the thoracic cavity. To treat pleural effusion, a physician conducts thoracentesis by carefully piercing the chest wall and entering...
240

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Related Experiment Video

Updated: Jun 22, 2025

Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
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Landmark Based Bronchoscope Localization for Needle Insertion Under Respiratory Deformation.

Inbar Fried1,2, Janine Hoelscher1, Jason A Akulian3

  • 1I. Fried, J. Hoelscher, S. Pizer, and R. Alterovitz are with the Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

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|July 1, 2024
PubMed
Summary
This summary is machine-generated.

Accurately locating a bronchoscope during lung cancer diagnosis is challenging due to lung motion. This new camera-based deep learning method precisely tracks the bronchoscope using airway landmarks, enabling more accurate biopsies.

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Area of Science:

  • Medical imaging
  • Robotics
  • Artificial intelligence

Background:

  • Bronchoscopy is the least invasive method for diagnosing lung cancer.
  • Accurate bronchoscope localization is critical for lung nodule biopsy.
  • Challenges include lung deformation, repetitive airway anatomy, and lack of features.

Purpose of the Study:

  • To introduce a real-time camera-based method for accurate bronchoscope localization.
  • To overcome limitations of global pose estimation using anatomical landmarks.
  • To enable precise needle insertion for lung biopsies.

Main Methods:

  • A deep learning approach for real-time bronchoscope localization.
  • Utilizing airway bifurcations as landmarks to account for deformation.
  • Estimating pose relative to distinct geometric features invariant to respiratory motion.

Main Results:

  • The method achieves sufficient accuracy for accessing small, clinically relevant lung nodules.
  • Demonstrated generalization across different patients and respiratory motion levels.
  • Effective localization even in challenging distal airways.

Conclusions:

  • The developed method enables precise bronchoscope localization for lung cancer diagnosis.
  • It overcomes intraoperative lung deformation and anatomical challenges.
  • It is a foundational step towards autonomous robotic bronchoscopy.