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Intraoperative Confocal Laser Scanning Microscopy With Use of AI for Optimized Surgical Excision of Basal Cell Carcinoma
Sponsor: LMU Klinikum
Summary
The aim is to use AI to assist surgeons in analyzing CLSM tissue slide images obtained during BCC surgeries with the aim to integrate it in real time. We plan to use AI to analyze CLSM images of BCCs and distinguish between tumor tissue, inflammatory tissue, and non-tumor/non-inflammatory tissue. This approach would provide surgeons with real-time feedback and automated image analysis, leading to a more targeted and efficient approach to tissue analysis. By improving the accuracy and speed of tissue analysis, our proposal could ultimately improve operative patient outcomes and benefit healthcare professionals.
Official title: Intraoperative Confocal Laser Scanning Microscopy and Artificial Intelligence for Optimized Surgical Excision of Basal Cell Carcinoma
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
1000
Start Date
2025-03-01
Completion Date
2027-12-31
Last Updated
2025-09-09
Healthy Volunteers
No
Conditions
Interventions
Ex vivo confocal microscopy
The aim is to use AI to assist surgeons in analyzing CLSM tissue slide images obtained during BCC surgeries with the aim to integrate it in real time. We plan to use AI to analyze CLSM images of BCCs and distinguish between tumor tissue, inflammatory tissue, and non-tumor/non-inflammatory tissue. This approach would provide surgeons with real-time feedback and automated image analysis, leading to a more targeted and efficient approach to tissue analysis. By improving the accuracy and speed of tissue analysis, our proposal could ultimately improve operative patient outcomes and benefit healthcare professionals.
Locations (1)
Clinic and Policlinic of Dermatology and Allergy, LMU Munich
Munich, Bavaria, Germany