Vision-based Detection and Tracking of Surgical Instruments
نویسنده
چکیده
Retained surgical items (RSIs) are surgical instruments, such as laparotomy sponges and suture needles, that are le in a patient’s body post-surgery. ese incredibly costly mistakes also pose a serious health risk. Manual methods of tracking are highly inaccurate at scale, and modern methods (including embedded RF chips) are costly and limited to larger objects. We implemented a vision-based tracking system using two mounted webcams that runs n the background and only alerts the user if an object is missing or if an object is in the incorrect area, as a proxy for quantifying contamination risk. We constrained our model to a set of ve surgical tools: laparotomy sponge, bovie tip, needle driver, surgical scissors and a needle counter box. We assembled and pre-processed our own dataset of 4650 images of these surgical items, and trained a Faster RCNN model on the data. Our resulting mAP@0.5IoU was .6109. We have identied vision-based surgical instrument tracking as a cost-eective and accurate alternative to traditional methods.
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