Xue Hu;Fabrizio Cutolo;Hisham Iqbal;Johann Henckel;Ferdinando Rodriguez y Baena
{"title":"人工智能驱动的膝关节手术增强现实无标记导航框架","authors":"Xue Hu;Fabrizio Cutolo;Hisham Iqbal;Johann Henckel;Ferdinando Rodriguez y Baena","doi":"10.1109/TAI.2024.3429048","DOIUrl":null,"url":null,"abstract":"Conventional orthopedic navigation systems depend on marker-based tracking, which may introduce additional skin incisions, increase the risk and discomfort for the patient, and entail increased workflow complexity. The guidance is conveyed via 2-D monitors, which may distract the surgeon and increase the cognitive burden. This study presents an artificial intelligence (AI)—driven surgical navigation framework for knee replacement surgery. The system comprises an augmented reality (AR) interface that combines an occlusions-robust deep learning-based markerless bone tracking and registration algorithm with a commercial HoloLens 2 headset calibrated for the user's perspective on both eyes. The feasibility of such a system in navigating a bone drilling task is investigated with an experienced orthopedic surgeon on three cadaveric knees under realistic operating room (OR) conditions. After registering an implant model to computed tomography (CT) scans, the preoperative plans are determined based on the location of the fixation pins. Navigation accuracy is quantified using a highly accurate optical tracking system. The achieved drilling error is 7.88 \n<inline-formula><tex-math>$\\pm$</tex-math></inline-formula>\n 2.41 mm in translation and 7.36 \n<inline-formula><tex-math>$\\pm$</tex-math></inline-formula>\n 1.77\n<inline-formula><tex-math>${}^{\\boldsymbol{\\circ}}$</tex-math></inline-formula>\n in orientation. The results demonstrate the viability of integrating AI and AR technology to navigate knee surgery.","PeriodicalId":73305,"journal":{"name":"IEEE transactions on artificial intelligence","volume":"5 10","pages":"5205-5215"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599938","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence-Driven Framework for Augmented Reality Markerless Navigation in Knee Surgery\",\"authors\":\"Xue Hu;Fabrizio Cutolo;Hisham Iqbal;Johann Henckel;Ferdinando Rodriguez y Baena\",\"doi\":\"10.1109/TAI.2024.3429048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Conventional orthopedic navigation systems depend on marker-based tracking, which may introduce additional skin incisions, increase the risk and discomfort for the patient, and entail increased workflow complexity. The guidance is conveyed via 2-D monitors, which may distract the surgeon and increase the cognitive burden. This study presents an artificial intelligence (AI)—driven surgical navigation framework for knee replacement surgery. The system comprises an augmented reality (AR) interface that combines an occlusions-robust deep learning-based markerless bone tracking and registration algorithm with a commercial HoloLens 2 headset calibrated for the user's perspective on both eyes. The feasibility of such a system in navigating a bone drilling task is investigated with an experienced orthopedic surgeon on three cadaveric knees under realistic operating room (OR) conditions. After registering an implant model to computed tomography (CT) scans, the preoperative plans are determined based on the location of the fixation pins. Navigation accuracy is quantified using a highly accurate optical tracking system. The achieved drilling error is 7.88 \\n<inline-formula><tex-math>$\\\\pm$</tex-math></inline-formula>\\n 2.41 mm in translation and 7.36 \\n<inline-formula><tex-math>$\\\\pm$</tex-math></inline-formula>\\n 1.77\\n<inline-formula><tex-math>${}^{\\\\boldsymbol{\\\\circ}}$</tex-math></inline-formula>\\n in orientation. The results demonstrate the viability of integrating AI and AR technology to navigate knee surgery.\",\"PeriodicalId\":73305,\"journal\":{\"name\":\"IEEE transactions on artificial intelligence\",\"volume\":\"5 10\",\"pages\":\"5205-5215\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599938\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on artificial intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10599938/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on artificial intelligence","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10599938/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial Intelligence-Driven Framework for Augmented Reality Markerless Navigation in Knee Surgery
Conventional orthopedic navigation systems depend on marker-based tracking, which may introduce additional skin incisions, increase the risk and discomfort for the patient, and entail increased workflow complexity. The guidance is conveyed via 2-D monitors, which may distract the surgeon and increase the cognitive burden. This study presents an artificial intelligence (AI)—driven surgical navigation framework for knee replacement surgery. The system comprises an augmented reality (AR) interface that combines an occlusions-robust deep learning-based markerless bone tracking and registration algorithm with a commercial HoloLens 2 headset calibrated for the user's perspective on both eyes. The feasibility of such a system in navigating a bone drilling task is investigated with an experienced orthopedic surgeon on three cadaveric knees under realistic operating room (OR) conditions. After registering an implant model to computed tomography (CT) scans, the preoperative plans are determined based on the location of the fixation pins. Navigation accuracy is quantified using a highly accurate optical tracking system. The achieved drilling error is 7.88
$\pm$
2.41 mm in translation and 7.36
$\pm$
1.77
${}^{\boldsymbol{\circ}}$
in orientation. The results demonstrate the viability of integrating AI and AR technology to navigate knee surgery.