Palpation-Based Multi-Tumor Detection Method Considering Moving Distance for Robot-assisted Minimally Invasive...

Area of Science:

• Robotics
• Surgical Technology
• Biomedical Engineering

Background:

• Robot-assisted minimally invasive surgery (RMIS) requires advanced tools for accurate tissue analysis.
• Current tumor detection methods in RMIS often struggle with identifying multiple tumors and optimizing sensor movement.
• There is a need for non-injurious, efficient palpation techniques in RMIS.

Purpose of the Study:

• To propose a novel palpation-based tumor detection method for RMIS.
• To develop a multi-tumor detection capability that overcomes limitations of single-tumor detection.
• To optimize the sensor's moving distance during palpation without compromising detection accuracy.

Main Methods:

• A tactile stiffness sensor utilizing piezoelectric vibration was designed for gentle tissue contact.
• A multi-tumor detection algorithm was developed to identify and locate multiple neoplastic tissues.
• A sampling strategy incorporating sensor moving distance was implemented for optimized palpation path planning.

Main Results:

• The proposed method successfully identified and located multiple tumors with high performance (F1 score > 0.99).
• Simulation studies demonstrated superior performance compared to existing tumor detection methods.
• The total moving distance of the sensor during palpation was reduced by 43%.

Conclusions:

• The novel palpation-based method enables accurate multi-tumor detection in RMIS.
• The integration of sensor movement optimization significantly enhances surgical efficiency.
• This technology offers a promising advancement for safer and more effective minimally invasive surgery.