Duration: January 2025 – December 2026
ID: PN-IV-P7-7.1-PED-2024-0959 / 46PED/2025
Status: Active
Domain: Biomedical Engineering, Robot-Assisted Surgery
An advanced RFID-based localization system for enhanced laparoscopic detection of small colorectal tumors. The IntelliSense system integrates radiofrequency identification technology with artificial intelligence to provide real-time, precise tumor localization during minimally invasive surgery, achieving detection distances of approximately 40mm through biological tissue.
Project Overview
The accurate detection and localization of small colorectal tumors during laparoscopic surgery presents a significant challenge for surgeons. Traditional imaging techniques often struggle to precisely identify tumor locations in real-time during minimally invasive procedures, potentially leading to incomplete resections or complications. This is particularly critical for small tumors where visual and tactile feedback is limited.
The IntelliSense project addresses this critical need by developing an optimized RFID system specifically designed for laparoscopic environments. The system combines miniaturized RFID tags implantable near tumor sites with advanced readers adapted for intra-operative use, enhanced by artificial intelligence algorithms for improved signal interpretation. Our preliminary analytical studies and laboratory tests have demonstrated the feasibility of achieving detection distances of approximately 40mm through biological tissue, while addressing challenges such as signal attenuation and electromagnetic interference in surgical environments.
This technology has the potential to significantly improve surgical outcomes by providing surgeons with precise, real-time localization of small tumors during laparoscopic colorectal surgery, ultimately enhancing patient safety and treatment effectiveness.
Partners & Acknowledgments
Technical University of Cluj-Napoca
Project Coordinator
Prof. Dr. Ing. Bogdan Mocan
Assoc. Prof. Mircea Fulea
Lec. Mircea Murar
Tehnologistic
Industrial Partner
Director: Ing. Albert Gyorgy
Project Lead: Ing. Mathe Zsolt
Ing. Zsolt Buzogany
Melinda Denezsi
Clinical Validation Partners
Medical institutions providing
ex-vivo and in-vivo testing
environments and expertise
This work is supported by a grant of the Ministry of Research, Innovation and Digitization, CCCDI – UEFISCDI, project number PN-IV-P7-7.1-PED-2024-0959, within PNCDI IV. Contract number: 46PED/2025 from January 13, 2025.
Project Objectives
Main Objective: To develop an optimized RFID system for laparoscopic surgery, integrate it with advanced artificial intelligence technologies, and test it on anatomical models, resulting in a functional prototype testable in advanced in-vivo scenarios on animal models.
- Design and develop a miniaturized RFID system for laparoscopy – To create biocompatible RFID tags and optimized antenna systems capable of operating effectively in the challenging electromagnetic environment of laparoscopic surgery, addressing signal attenuation through biological tissue.
- Develop an adapted RFID reader for intra-operative use – To design and manufacture a specialized RFID reader system optimized for surgical environments, with automatic calibration protocols and enhanced signal-to-noise ratio (SNR) optimization to ensure reliable detection in the presence of interference.
- Implement AI software for RFID data interpretation – To develop machine learning algorithms and neural networks for advanced signal filtering, pattern detection, and real-time data analysis, significantly improving detection accuracy and reducing false positives.
- Test the system on advanced medical specimens for clinical validation – To conduct comprehensive ex-vivo testing on animal and human tissue specimens, followed by in-vivo validation on animal models, comparing performance with conventional imaging techniques (CT, MRI, ultrasound) and preparing for TRL 4/5.
Results & Outcomes
Preliminary Results
The research team has completed extensive preliminary analytical simulations and laboratory tests that demonstrate the feasibility of the IntelliSense concept. Key achievements include comprehensive studies on RFID signal attenuation through biological tissue (0-20mm depth), demonstrating exponential decay patterns influenced by tissue conductivity and permittivity. The team has also optimized Signal-to-Noise Ratio (SNR) under varying interference conditions, establishing baseline system effectiveness.
Laboratory validation using a 134 kHz RFID receiver with custom-designed 700 micro-Henry antenna has shown promising results. Testing was conducted in both air and saline solution (9mg/ml NaCl concentration) across multiple angular positions of both receiver antenna (-90° to +90°) and RFID tag orientations (0° to 90°). Detection distances proved satisfactory across most configurations, with the system successfully identifying consecutive 128-bit data packets at target distances.
Expected Outcomes
- Functional IntelliSense prototype achieving approximately 40mm detection distance through biological tissue
- AI-enhanced signal processing algorithms with advanced filtering and pattern recognition capabilities
- Medical-grade user interface integrated with laparoscopic equipment and haptic feedback systems
- Comprehensive validation data from ex-vivo testing on animal colonic specimens and human tissue samples
- In-vivo animal testing results demonstrating clinical feasibility
- 4-6 publications in Q1 journals covering system design, signal optimization, biological environment challenges, AI integration, and comparative studies
Project Milestones
- December 5, 2025: First reporting period – Initial IntelliSense prototype complete, preliminary laboratory testing finished, first 3 journal articles submitted
- October 31, 2026: Second reporting period – Improved prototype complete, extensive ex-vivo and in-vivo validation testing completed, additional 3 journal articles submitted
- December 31, 2026: Project completion – Final prototype delivered, comprehensive validation report, full dissemination of results
The gallery showcases preliminary analytical simulations, laboratory test configurations, and initial validation results demonstrating system feasibility.
Publications & Outputs
Planned Journal Articles (Q1 Journals)
“Advanced RFID-Based Localization System for Small Tumor Detection in Laparoscopic Surgery”
Focus: Design and development of the IntelliSense RFID system for intra-operative localization of small tumors. Covers hardware design, operating room integration, and comparative precision with other methods.
Status: Planned for 2025
“Optimization of RFID Signal Processing for Biomedical Applications: A Case Study on Tumor Detection”
Focus: RFID signal processing optimization for medical applications. Covers noise filtering algorithms, signal calibration, and testing on biological phantoms.
Status: Planned for 2025
“Evaluation of RFID Sensor Performance in Biological Environments: Challenges and Solutions”
Focus: Analysis of biological environment impact on RFID system performance. Addresses signal attenuation in tissues and solutions for improving reliability.
Status: Planned for 2025
“Development of a Portable RFID-Based Device for Enhanced Laparoscopic Tumor Localization”
Focus: Creation of a portable RFID device for laparoscopic surgery. Covers modular design, medical imaging integration, and usage scenarios.
Status: Planned for 2026
“Machine Learning-Enhanced RFID Systems for Real-Time Tumor Detection: A Feasibility Study”
Focus: Using AI to improve RFID-based tumor detection. Covers classification algorithms, RFID signal pattern analysis, and experimental validation.
Status: Planned for 2026
“Comparative Study of RFID and Conventional Imaging Techniques for Small Tumor Localization”
Focus: Performance comparison of RFID with MRI, CT, and ultrasound. Analyzes sensitivity, specificity, advantages and limitations of each method.
Status: Planned for 2026
Additional Planned Publications
Additional articles are planned covering AI-driven signal enhancement using deep learning (CNN, RNN), fusion of RFID and AI for intelligent tumor localization, and comprehensive ex-vivo and in-vivo testing results on animal models.
Acknowledgment for all publications: “This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CCCDI – UEFISCDI, project number PN-IV-P7-7.1-PED-2024-0959, within PNCDI IV.”
Impact & Future Applications
The IntelliSense system has significant potential to transform laparoscopic colorectal surgery by providing surgeons with real-time, precise localization of small tumors that are difficult to detect using conventional methods. This technology addresses a critical clinical need, as incomplete tumor resection due to inadequate localization can lead to cancer recurrence and additional surgical interventions. By achieving detection distances of approximately 40mm through biological tissue, IntelliSense offers a practical solution that can be integrated into existing surgical workflows.
Beyond colorectal cancer, the technology has broader applications in detecting and localizing other small tumors throughout the abdomen and pelvis during minimally invasive procedures. The integration of artificial intelligence for signal enhancement and pattern recognition represents a significant advancement in surgical guidance technology. Future development directions include miniaturization for use in other surgical contexts, integration with augmented reality surgical navigation systems, and expansion to additional cancer types. The system’s modular design and AI-enhanced capabilities position it well for commercialization and widespread clinical adoption, potentially improving outcomes for thousands of cancer patients annually while reducing healthcare costs through more effective single-stage surgical interventions.
Last updated: January 2025 | Project Duration: 24 months (January 2025 – December 2026)