Room: Karl Dean Ballroom A2
Purpose: To develop a convenient, robust and label-free method to individually track TLD-100 chips and their calibration.
Methods: To register TLD-100 by their unique surface texture, 752 images were captured using Opti-Tekscope OT-V1 digital microscope camera for both sides of 376 TLD-100 chips. A median intensity thresholding method was used to segment images into foreground and background. Affine transformation was used to register the segmented images to the same position. The â€œfinger printâ€? of each image was calculated from its registered image. All â€œfinger printsâ€? were recorded to an Elasticsearch search engine database that allows for real-time searching, creating a library of TLD â€œfinger printsâ€? for future matching. Each time a TLD returned to the inventory after dosimetric reading, new images were taken from both sides of the TLD and two finger prints were generated to search for matches within the database based on normalized cross-correlation that was robust to variations in lighting conditions.
Results: The average time for registering and matching one image was 9s and 1.3s, respectively. The finger print match was repeated three times for all TLD chips. In each of the three repetitions of 752 image matches, 4, 3, and 7 images did not find a match. The single-side failure rates were thus 0.5%, 0.4%, and 0.9%, respectively. However, none of the TLDs failed both sides, resulting in a 100% success rate in identifying these chips when images of both sides were taken.
Conclusion: This work proposed and tested a novel label-free method to identify individual TLD chips without the complicated and fragile inventory management previously used to track individual TLDs. This method will enable more accurate TLD dosimetry based on individual calibration.
Funding Support, Disclosures, and Conflict of Interest: NIH U19AI067769 DE-SC0017687 NIH R21CA228160 DE-SC0017057 NIH R44CA183390 NIH R43CA183390 NIH R01CA188300