Please use this identifier to cite or link to this item:
|Title:||Development of an AI solution for surgical gauze management||Authors:||Lee, Yun Fai||Keywords:||Engineering::Mechanical engineering||Issue Date:||2022||Publisher:||Nanyang Technological University||Source:||Lee, Y. F. (2022). Development of an AI solution for surgical gauze management. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158345||Abstract:||Gossypiboma, the accidental retainment of gauze in a patient’s body is a potentially fatal problem that persists on due to human error. This error not only affects the patient but also affect the hospital in the form of reputation loss and lawsuits that result in large monetary losses. Over the years, several solutions such as manual counting standard operating procedures, X-Ray detectable gauzes and RFID-tagged surgical gauzes were implemented with limited success. These solutions functioned as secondary safety-nets and in a limited extent assisted in further reducing the odds for Gossypiboma. However, these methods are still too expensive and inefficient for long term use. As such, this project demonstrates a functional and practical smart system solution that can support medical staff in the Operation Theatre in the prevention of Gossypiboma in a more efficient and effective manner. Several new technologies such as Computer Vision, Transfer Learning and Edge Computing were investigated and integrated to develop a smart solution for Surgical Gauze Management. With the advancements made in this new system till date, it can keep track of gauzes used during surgery with a high accuracy of 99.7% and process its video feed at 12 Frames Per Second, enabling real-time usage. It is also compatible with the current standard operating procedure in Singapore General Hospital. The main objective of developing a smart system solution that can support the medical staff in reducing human error in the aspect of Surgical Gauze Management in the Operation Theatre was achieved.||URI:||https://hdl.handle.net/10356/158345||Fulltext Permission:||embargo_restricted_20240517||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Student Reports (FYP/IA/PA/PI)|
Files in This Item:
|Lee Yun Fai FYP Dr-NTU.pdf|
|3.09 MB||Adobe PDF||Under embargo until May 17, 2024|
Updated on Jun 23, 2022
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.