Premium
Fast‐MICP for frameless image‐guided surgery
Author(s) -
Lee JiannDer,
Huang ChungHsien,
Wang ShengTa,
Lin ChungWei,
Lee ShinTseng
Publication year - 2010
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3470097
Subject(s) - fiducial marker , iterative closest point , computer vision , artificial intelligence , computer science , image registration , medical imaging , image guided surgery , augmented reality , projector , patient registration , image (mathematics) , point cloud
Purpose: In image‐guided surgery (IGS) systems, image‐to‐physical registration is critical for reliable anatomical information mapping and spatial guidance. Conventional stereotactic frame‐based or fiducial‐based approaches provide accurate registration but are not patient‐friendly. This study proposes a frameless cranial IGS system that uses computer vision techniques to replace the frame or fiducials with the natural features of the patient. Methods: To perform a cranial surgery with the proposed system, the facial surface of the patient is first reconstructed by stereo vision. Accuracy is ensured by capturing parallel‐line patterns projected from a calibrated LCD projector. Meanwhile, another facial surface is reconstructed from preoperative computed tomography (CT) images of the patient. The proposed iterative closest point (ICP)‐based algorithm [fast marker‐added ICP (Fast‐MICP)] is then used to register the two facial data sets, which transfers the anatomical information from the CT images to the physical space. Results: Experimental results reveal that the Fast‐MICP algorithm reduces the computational cost of marker‐added ICP (J.‐D. Lee et al. , “A coarse‐to‐fine surface registration algorithm for frameless brain surgery,” in Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, pp. 836–839) to 10% and achieves comparable registration accuracy, which is under 3 mm target registration error (TRE). Moreover, two types of optical‐based spatial digitizing devices can be integrated for further surgical navigation. Anatomical information or image‐guided surgical landmarks can be projected onto the patient to obtain an immersive augmented reality environment. Conclusion: The proposed frameless IGS system with stereo vision obtains TRE of less than 3 mm. The proposed Fast‐MICP registration algorithm reduces registration time by 90% without compromising accuracy.