Experimental Endoscope Rotitome-G: A pixel-by-pixel erasure microsurgical endoscopic sarcotome for resection of soft tissue tumours in closed body cavities

Harjeet Singh Gandhi

doi:10.24297/ijct.v22i.9327

Authors

Harjeet Singh Gandhi Hamilton Health Sciences, Ontario

DOI:

https://doi.org/10.24297/ijct.v22i.9327

Keywords:

Flexible micro-endoscope, Neuroendoscopy, Optoelectronics, Neuronavigation, Brain shift, Brain biomechanics, Glioblastoma, Brain tumours, Neurosurgery

Abstract

Background: The procedure of minimal access to the brain through the nose is an ancient practice. However, endoscopic entry via a burr hole has recently gained significant traction in the practice of neurosurgery. High-resolution endoscopic images are possible with limited admittance of accessory tools and instruments. Although brain tissue can be removed easily with a suction device, but it will be uncontrolled ‘excision’. The Rotitome-G is a precision micro-endoscopic target access surgical instrument. It has several accessories for intraoperative assessment and precise removal of the soft tissue lesions pixel-by-pixel within a closed body cavity through a single portal.

Objective: This preliminary theoretical research study on Rotitome-G is transition to experimental cadaveric and clinical studies. It describes the construction and mechanics of this newly conceptualized robot-assisted microsurgical endoscope. The design includes precise excision at the pixel and microscopic level and removes tissue debris under computer-aided navigation and direct instrument vision. Currently, the primary objective is to interest both the neurosurgeons and biomedical engineers, hence its contents are diverse resulting in an extended text.

Methodology: The study provides the basics of computer vision techniques and neuronavigation to establish the function and application of the Rotitome-G. The structure and kinematics of the animalcule Rotifer have been considered followed by the construction of Rotitome-G. For a better understanding of intracranial tumour excision, the article examines the role of intra-operative imaging, biomechanics of brain tissue, and brain shift to better understand the principles of this newly conceived microsurgical instrument. The functional capabilities of the instrument have been putatively demonstrated by describing the excision of a glioblastoma.

Conclusion: It is expected that the key design of Rotitome-G would meet the goal of neurosurgical resection by excising maximum amount of pathological tissue. Direct microscopic resection will prevent damage to the eloquent areas to improve the prognosis by limiting neurological morbidity. Clinical validity of the Rotitome -G remains to be determined.

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References

A., T., Hayashi, S., Nagayama, K., & Watanabe, I. (2007). Mechanical Characterization of Brain Tissue in High-Rate Compression. J Biomech. Sci Eng, 2(3), 115–126. https://doi.org/DOI: 10.1299/jbse.2.115

Ainger, R., & Gillquist, J. (n.d.). Arthoscopy of the knee. Thieme Medical Publishers, 1991, New York.

Barnholtz-Sloan, J. S., Ostrom, Q. T., & Cote, D. (2018). Epidemiology of Brain Tumors. In Neurologic Clinics. https://doi.org/10.1016/j.ncl.2018.04.001

Basser, P. J., Mattiello, J., & LeBihan, D. (1994). MR diffusion tensor spectroscopy and imaging. Biophysical Journal. https://doi.org/10.1016/S0006-3495(94)80775-1

Bedard, N., Quang, T., Schmeler, K., Richards-Kortum, R., & Tkaczyk, T. S. (2012). Real-time video mosaicing with a high-resolution microendoscope. Biomedical Optics Express. https://doi.org/10.1364/boe.3.002428

Bhandari, A., Koppen, J., & Agzarian, M. (2020). Convolutional neural networks for brain tumour segmentation. Insights into Imaging, 11(1). https://doi.org/10.1186/s13244-020-00869-4

Bilston, L., Clarke, E., & Cheng, S. (2008). Brain tissue mechanical properties – making sense of 5 decades of test data. In A. Gefen (Ed.), The pathomechanics of tissue injury and disease, and the mechano-physiology of healing (pp. 1–18). Kerala Research Sign Post.

Black, P. M. L., Moriarty, T., Alexander, E., Stieg, P., Woodard, E. J., Gleason, P. L., Martin, C. H., Kikinis, R., Schwartz, R. B., & Jolesz, F. A. (1997). Development and implementation of intraoperative magnetic resonance imaging and its neurosurgical applications. Neurosurgery. https://doi.org/10.1097/00006123-199710000-00013

Blond, S., Lejeune, J. P., Dupard, T., Parent, M., Clarisse, J., & Christiaens, J. L. (1991). The stereotactic approach to brain stem lesions: a follow-up of 29 cases. Acta Neurochirurgica. Supplementum. https://doi.org/10.1007/978-3-7091-9160-6_21

Carton, F.-X., Chabanas, M., le Lann, F., & Noble, J. H. (2020). Automatic segmentation of brain tumor resections in intraoperative ultrasound images using U-Net. Journal of Medical Imaging, 7(03). https://doi.org/10.1117/1.jmi.7.3.031503

Cheng, S., Clarke, E. C., & Bilston, L. E. (2008). Rheological properties of the tissues of the central nervous system: A review. In Medical Engineering and Physics. https://doi.org/10.1016/j.medengphy.2008.06.003

Coté, G. L., Lec, R. M., & Pishko, M. V. (2003). Emerging biomedical sensing technologies and their applications. IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2003.814656

De Witt Hamer, P. C., Robles, S. G., Zwinderman, A. H., Duffau, H., & Berger, M. S. (2012). Impact of intraoperative stimulation brain mapping on glioma surgery outcome: A meta-analysis. In Journal of Clinical Oncology. https://doi.org/10.1200/JCO.2011.38.4818

Elias, W. J., Fu, K. M., & Frysinger, R. C. (2007). Cortical and subcortical brain shift during stereotactic procedures. Journal of Neurosurgery. https://doi.org/10.3171/JNS-07/11/0983

Fallenstein, G. T., Hulce, V. D., & Melvin, J. W. (1969). Dynamic mechanical properties of human brain tissue. Journal of Biomechanics. https://doi.org/10.1016/0021-9290(69)90079-7

Gandhi, H. S. (2022a). A Comprehensive Review of Computer Vision Techniques to Interest Physicians and Surgeons, Role of A Clinical Biomechanical Engineer in Pre-Operative Surgical Planning, And Preamble To HSG-Amoeba, A New Concept of Biomedical Image Modeling Technique. International Journal of Computers and Technology, Vol. 22 (2022), 1–49. https://doi.org/10.24297/ijct.v22i.9219

Gandhi, H. S. (2022b). Hyalite Sol-Gel Amoeba: A Physiology-Based Biophysical Model for Segmentation and Biotransformation of Medical Images To 3D Solid-State Characterizing Native Tissue Properties for Patient-Specific and Patient-Appropriate Analysis for Surgical Applications. International Journal of Computers & Technology, 22, 64–85. https://doi.org/10.24297/ijct.v22i.9228

Gerard, I. J., Kersten-Oertel, M., Petrecca, K., Sirhan, D., Hall, J. A., & Collins, D. L. (2017). Brain shift in neuronavigation of brain tumors: A review. In Medical Image Analysis. https://doi.org/10.1016/j.media.2016.08.007

Gergel, I., Hering, J., Tetzlaff, R., Meinzer, H. P., & Wegner, I. (2011). An electromagnetic navigation system for transbronchial interventions with a novel approach to respiratory motion compensation. Medical Physics. https://doi.org/10.1118/1.3662871

Grant, B. D., Quang, T., Possati-Resende, J. C., Scapulatempo-Neto, C., de Macedo Matsushita, G., Mauad, E. C., Stoler, M. H., Castle, P. E., Guerreiro Fregnani, J. H. T., Schmeler, K. M., & Richards-Kortum, R. (2019). A mobile-phone based high-resolution microendoscope to image cervical precancer. PLoS ONE. https://doi.org/10.1371/journal.pone.0211045

Harlaar, N., van Dam, G., & Ntziachristos, V. (2014). Intraoperative optical imaging. In F. A. Jolesz (Ed.), Intraoperative Imaging and Image-Guided Therapy (pp. 233–245). Springer Science+Business Media.

Hartkens, T., Hill, D. L. G., Castellano-Smith, A. D., Hawkes, D. J., Maurer, C. R., Martin, A. J., Hall, W. A., Liu, H., & Truwit, C. L. (2003). Measurement and analysis of brain deformation during neurosurgery. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/TMI.2002.806596

Hata, N. (2014). Surgical Navigation Technology. In F. Jolesz (Ed.), Intraoperative Imaging and Image-Guided Therapy (Ed, pp. 249–257). Springer Science+Business Media. https://doi.org/10.1007/978-1-4614-7657-3_17

Hoshide, R., & Teo, C. (2017). Neuroendoscopy to Achieve Superior Glioma Resection Outcomes. Clinical Neurosurgery. https://doi.org/10.1093/neuros/nyx274

Intraoperative Imaging and Image-Guided Therapy. (2014). In Intraoperative Imaging and Image-Guided Therapy. https://doi.org/10.1007/978-1-4614-7657-3

Iseki, H., Nakamura, R., Muragaki, Y., Suzuki, T., Chernov, M., Hori, T., & Takakura, K. (2008). Advanced computer-aided intraoperative technologies for information-guided surgical management of gliomas: Tokyo Women’s Medical University Experience. Minimally Invasive Neurosurgery. https://doi.org/10.1055/s-0028-1082333

Ivan, M. E., Yarlagadda, J., Saxena, A. P., Martin, A. J., Starr, P. A., Sootsman, W. K., & Larson, P. S. (2014). Brain shift during bur hole-based procedures using interventional MRI: Clinical article. Journal of Neurosurgery. https://doi.org/10.3171/2014.3.JNS121312

Ivarsson J, V. D. C. L. P. (2000). Strain relief from the cerebral ventricles during head impact: Experimental studies on natural protection of the brain. Journal of Biomechanics, 33(2), 181–189.

Iversen, D. H., Wein, W., Lindseth, F., Unsgård, G., & Reinertsen, I. (2018). Automatic Intraoperative Correction of Brain Shift for Accurate Neuronavigation. World Neurosurgery. https://doi.org/10.1016/j.wneu.2018.09.012

Jenkinson, M. D., Barone, D. G., Bryant, A., Vale, L., Bulbeck, H., Lawrie, T. A., Hart, M. G., & Watts, C. (2018). Intraoperative imaging technology to maximise extent of resection for glioma. In Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD012788.pub2

Jolesz, F. A., Lorensen, W. E., Shinmoto, H., Atsumi, H., Nakajima, S., Kavanaugh, P., Saiviroonporn, P., Seltzer, S. E., Silverman, S. G., Phillips, M., & Kikinis, R. (1997). Perspective. Interactive virtual endoscopy. In American Journal of Roentgenology. https://doi.org/10.2214/ajr.169.5.9353433

Kacher, D. F., Whalen, B., Handa, A., & Jolesz, F. A. (2014). The Advanced Multimodality Image-Guided Operating (AMIGO) Suite. In Intraoperative Imaging and Image-Guided Therapy. https://doi.org/10.1007/978-1-4614-7657-3_24

Karkenny, A. J., Mendelis, J. R., Geller, D. S., & Gomez, J. A. (2019). The Role of Intraoperative Navigation in Orthopaedic Surgery. Journal of the American Academy of Orthopaedic Surgeons. https://doi.org/10.5435/jaaos-d-18-00478

Kelly, P. J., Kall, B. A., Goerss, S., & Earnest, F. (1986). Computer-assisted stereotaxic laser resection of intra-axial brain neoplasms. Journal of Neurosurgery. https://doi.org/10.3171/jns.1986.64.3.0427

Khuri-Yakub, B. T., & Oralkan, Ö. (2011). Capacitive micromachined ultrasonic transducers for medical imaging and therapy. Journal of Micromechanics and Microengineering. https://doi.org/10.1088/0960-1317/21/5/054004

Kleihues, P., Louis, D. N., Scheithauer, B. W., Rorke, L. B., Reifenberger, G., Burger, P. C., & Cavenee, W. K. (2002). The WHO classification of tumors of the nervous system. Journal of Neuropathology and Experimental Neurology. https://doi.org/10.1093/jnen/61.3.215

Li, K. W., Nelson, C., Suk, I., & Jallo, G. I. (2005). Neuroendoscopy: past, present, and future. In Neurosurgical focus (Vol. 19, Issue 6). https://doi.org/10.3171/foc.2005.19.6.2

Li, Y. M., Suki, D., Hess, K., & Sawaya, R. (2016). The influence of maximum safe resection of glioblastoma on survival in 1229 patients: Can we do better than gross-total resection? Journal of Neurosurgery. https://doi.org/10.3171/2015.5.JNS142087

Mansouri, A., Mansouri, S., Hachem, L. D., Klironomos, G., Vogelbaum, M. A., Bernstein, M., & Zadeh, G. (2016). The role of 5-aminolevulinic acid in enhancing surgery for high-grade glioma, its current boundaries, and future perspectives: A systematic review. In Cancer. https://doi.org/10.1002/cncr.30088

Maurer, C. R., Hill, D. L. G., Maciunas, R. J., Barwise, J. A., Fitzpatrick, J. M., & Wang, M. Y. (1998). Measurement of intraoperative brain surface deformation under a craniotomy. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1097/00006123-199809000-00066

McGirt, M. J., Mukherjee, D., Chaichana, K. L., Than, K. D., Weingart, J. D., & Quinones-Hinojosa, A. (2009). Association of surgically acquired motor and language deficits on overall survival after resection of glioblastoma multiforme. Neurosurgery. https://doi.org/10.1227/01.NEU.0000349763.42238.E9

Mittal, S., & Black, P. M. (2006). Intraoperative magnetic resonance imaging in neurosurgery: the Brigham concept. In Acta neurochirurgica. Supplement. https://doi.org/10.1007/978-3-211-33303-7_11

Motkoski, J., & Sutherland, G. (2014). Progress in Neurosurgical Robotics. In F. A. Jolesz (Ed.), Intraoperative Imaging and Image-Guided Therapy (ed, pp. 601–612). Springer Science+Business Media.

Muldoon, T. J., Pierce, M. C., Nida, D. L., Williams, M. D., Gillenwater, A., & Richards-Kortum, R. (2007). Subcellular-resolution molecular imaging within living tissue by fiber microendoscopy. Optics Express. https://doi.org/10.1364/oe.15.016413

Nakaji, P., & Spetzler, R. F. (2004). Innovations in surgical approach: the marriage of technique, technology, and judgment. Clinical Neurosurgery.

Nimsky, C., Ganslandt, O., Kober, H., Buchfelder, M., & Fahlbusch, R. (2001). Intraoperative magnetic resonance imaging combined with neuronavigation: A new concept. Neurosurgery. https://doi.org/10.1227/00006123-200105000-00023

Novotny, J., Vymazal, J., Novotny, J., Tlachacova, D., Schmitt, M., Chuda, P., Urgosik, D., & Liscak, R. (2005). Does new magnetic resonance imaging technology provide better geometrical accuracy during stereotactic imaging? Journal of Neurosurgery. https://doi.org/10.3171/jns.2005.102.s_supplement.0008

Ogawa, S., Tank, D. W., Menon, R., Ellermann, J. M., Kim, S. G., Merkle, H., & Ugurbil, K. (1992). Intrinsic signal changes accompanying sensory stimulation: Functional brain mapping with magnetic resonance imaging. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.89.13.5951

Pallud, J., Varlet, P., Devaux, B., Geha, S., Badoual, M., Deroulers, C., Page, P., Dezamis, E., Daumas-Duport, C., & Roux, F. X. (2010). Diffuse low-grade oligodendrogliomas extend beyond MRI-defined abnormalities. Neurology. https://doi.org/10.1212/WNL.0b013e3181e04264

Panciani, P. P., Fontanella, M., Schatlo, B., Garbossa, D., Agnoletti, A., Ducati, A., & Lanotte, M. (2012). Fluorescence and image guided resection in high grade glioma. Clinical Neurology and Neurosurgery. https://doi.org/10.1016/j.clineuro.2011.09.001

Pohl, K., Bouix, S., Shenton, M., Grimson, W., & Kikinis, R. (2007). Automatic segmentation using non-rigid registration. Med Image Comput Comput Assist Interv, 26(9), 1201–1212.

Rahman, M., Murad, G. J. A., & Mocco, J. (2009). Early history of the stereotactic apparatus in neurosurgery. Neurosurgical Focus. https://doi.org/10.3171/2009.7.FOCUS09118

Regula, J., MacRobert, A. J., Gorchein, A., Buonaccorsi, G. A., Thorpe, S. M., Spencer, G. M., Hatfield, A. R. W., & Bown, S. G. (1995). Photosensitisation and photodynamic therapy of oesophageal, duodenal, and colorectal tumours using 5 aminolaevulinic acid induced protoporphyrin IX - a pilot study. Gut. https://doi.org/10.1136/gut.36.1.67

Reyns, N., Leroy, H. A., Delmaire, C., Derre, B., Le-Rhun, E., & Lejeune, J. P. (2017). Intraoperative MRI for the management of brain lesions adjacent to eloquent areas. Neurochirurgie. https://doi.org/10.1016/j.neuchi.2016.12.006

Roberts, D. W., Hartov, A., Kennedy, F. E., Miga, M. I., & Paulsen, K. D. (1998). Intraoperative brain shift and deformation: A quantitative analysis of cortical displacement in 28 cases. Neurosurgery. https://doi.org/10.1097/00006123-199810000-00010

Sanai, N., & Berger, M. S. (2008). Glioma extent of resection and its impact on patient outcome. In Neurosurgery. https://doi.org/10.1227/01.neu.0000318159.21731.cf

Schonberg, T., Pianka, P., Hendler, T., Pasternak, O., & Assaf, Y. (2006). Characterization of displaced white matter by brain tumors using combined DTI and fMRI. NeuroImage. https://doi.org/10.1016/j.neuroimage.2005.11.015

Senft, C., Bink, A., Franz, K., Vatter, H., Gasser, T., & Seifert, V. (2011). Intraoperative MRI guidance and extent of resection in glioma surgery: A randomised, controlled trial. The Lancet Oncology. https://doi.org/10.1016/S1470-2045(11)70196-6

Shim, K. W., Park, E. K., Kim, D. S., & Choi, J. U. (2017). Neuroendoscopy: Current and future perspectives. In Journal of Korean Neurosurgical Society (Vol. 60, Issue 3). https://doi.org/10.3340/jkns.2017.0202.006

Stummer, W., Stocker, S., Wagner, S., Stepp, H., Fritsch, C., Goetz, C., Goetz, A. E., Kiefmann, R., & Reulen, H. J. (1998). Intraoperative detection of malignant gliomas by 5-aminolevulinic acid- induced porphyrin fluorescence. Neurosurgery. https://doi.org/10.1097/00006123-199803000-00017

Takhounts, E. G., Crandall, J. R., & Darvish, K. (2003). On the Importance of Nonlinearity of Brain Tissue under Large Deformations. SAE Technical Papers. https://doi.org/10.4271/2003-22-0005

Taniguchi, H., Muragaki, Y., Iseki, H., Nakamura, R., & Taira, T. (2006). New radiofrequency coil integrated with a stereotactic frame for intraoperative MRI-controlled stereotactically guided brain surgery. Stereotactic and Functional Neurosurgery. https://doi.org/10.1159/000094845

Taniguchi, M., Cedzich, C., Taniguchi, M., Cedzich, C., & Schramm, J. (1993). Modification of cortical stimulation for motor evoked potentials under general anesthesia: Technical description. Neurosurgery. https://doi.org/10.1227/00006123-199302000-00011

Trout, J. M., Walsh, E. J., & Fayer, R. (2002). Rotifers Ingest Giardia Cysts. The Journal of Parasitology. https://doi.org/10.2307/3285557

Tsugu, A., Ishizaka, H., Mizokami, Y., Osada, T., Baba, T., Yoshiyama, M., Nishiyama, J., & Matsumae, M. (2011). Impact of the combination of 5-aminolevulinic acid-induced fluorescence with intraoperative magnetic resonance imaging-guided surgery for glioma. In World Neurosurgery. https://doi.org/10.1016/j.wneu.2011.02.005

Tunnacliffe, A., & Lapinski, J. (2003). Resurrecting Van Leeuwenhoek’s rotifers: A reappraisal of the role of disaccharides in anhydrobiosis. In Philosophical Transactions of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rstb.2002.1214

Wallace, R. L. (2002). Rotifers: Exquisite metazoans. Integrative and Comparative Biology.

Warfield, S. K., Haker, S. J., Talos, I. F., Kemper, C. A., Weisenfeld, N., Mewes, A. U. J., Goldberg-Zimring, D., Zou, K. H., Westin, C. F., Wells, W. M., Tempany, C. M. C., Golby, A., Black, P. M., Jolesz, F. A., & Kikinis, R. (2005). Capturing intraoperative deformations: Research experience at Brigham and Women’s hospital. Medical Image Analysis. https://doi.org/10.1016/j.media.2004.11.005

Warfield, S. K., Nabavi, A., Butz, T., Tuncali, K., Silverman, S. G., Black, P. M. L., Jolesz, F. A., & Kikinis, R. (2000). Intraoperative segmentation and nonrigid registration for image guided therapy. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1007/978-3-540-40899-4_18

Wen, P. Y., & Kesari, S. (2008). Malignant gliomas in adults. In New England Journal of Medicine. https://doi.org/10.1056/NEJMra0708126

Wittek, A., Grosland, N. M., Joldes, G. R., Magnotta, V., & Miller, K. (2016). From Finite Element Meshes to Clouds of Points: A Review of Methods for Generation of Computational Biomechanics Models for Patient-Specific Applications. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-015-1469-2

Wittek, A., Miller, K., Kikinis, R., & Warfield, S. K. (2007). Patient-specific model of brain deformation: Application to medical image registration. Journal of Biomechanics. https://doi.org/10.1016/j.jbiomech.2006.02.021

Woodworth, G., McGirt, M. J., Samdani, A., Garonzik, I., Olivi, A., & Weingart, J. D. (2005). Accuracy of frameless and frame-based image-guided stereotactic brain biopsy in the diagnosis of glioma: Comparison of biopsy and open resection specimen. Neurological Research. https://doi.org/10.1179/016164105X40057

Wu, J. S., Zhou, L. F., Tang, W. J., Mao, Y., Hu, J., Song, Y. Y., Hong, X. N., & Du, G. H. (2007). Clinical evaluation and follow-up outcome of diffusion tensor imaging-based functional neuronavigation: A prospective, controlled study in patients with gliomas involving pyramidal tracts. Neurosurgery. https://doi.org/10.1227/01.neu.0000303189.80049.ab

Wygant, I. O., Zhuang, X., Yeh, D. T., Oralkan, Ö., Ergun, A. S., Karaman, M., & Khuri-Yakub, B. T. (2008). Integration of 2D CMUT arrays with front-end electronics for volumetric ultrasound imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. https://doi.org/10.1109/TUFFC.2008.652

Xu, L., Lin, Y., Han, J. C., Xi, Z. N., Shen, H., & Gao, P. Y. (2007). Magnetic resonance elastography of brain tumors: Preliminary results. Acta Radiologica. https://doi.org/10.1080/02841850701199967

Yan, J. L., Van Der Hoorn, A., Larkin, T. J., Boonzaier, N. R., Matys, T., & Price, S. J. (2017). Extent of resection of peritumoral diffusion tensor imaging-detected abnormality as a predictor of survival in adult glioblastoma patients. In Journal of Neurosurgery. https://doi.org/10.3171/2016.1.JNS152153

Yaniv, Z., Wilson, E., Lindisch, D., & Cleary, K. (2009). Electromagnetic tracking in the clinical environment. Medical Physics. https://doi.org/10.1118/1.3075829

Yasargil, & MG. (1969). Microsurgery Applied to Neurosurgery. Georg Thieme Verlag / Academic Press,.

Yrjänä, S. K., Tuominen, J., & Koivukangas, J. (2007). Intraoperative magnetic resonance imaging in neurosurgery. In Acta Radiologica. https://doi.org/10.1080/02841850701280858

Zhao, L., & Jolesz, F. A. (2014). Navigation with the Integration of Device Tracking and Medical Imaging. In F.A. Jolesz (Ed.), Intraoperative Imaging and Image-Guided Therapy (Ed, pp. 259–276). Springer Science+Business Media. https://doi.org/10.1007/978-1-4614-7657-3_17