Publications

Please see my Google Scholar for details.

PDF copies of articles published since joining Carleton University can be found below.

Full List of Publications

[1] U. Tanin, A. Duimering, C. Law, J. Ruzicki, G. Luna, and M. S. Holden, “Performance evaluation in cataract surgery with an ensemble of 2d-3d convolutional neural networks,” in Healthcare Technology Letters, 2024. [ bib | DOI | .pdf ]
[2] G. Salame, M. S. Holden, B. P. Lucas, and A. Portillo, “Change in economy of ultrasound probe motion among general medicine trainees,” The Ultrasound Journal, vol. 16, no. 1, p. 5, 2024. [ bib | DOI | .pdf ]
[3] J. Bierbrier, R. Hisey, J. Yang, A. Duimering, C. Law, G. Fichtinger, and M. S. Holden, “Video-based phase recognition in cataract surgery.” Imaging Network Ontario, 2024. [ bib ]
[4] J. Yang, R. Hisey, J. Bierbrier, C. Law, G. Fichtinger, and M. S. Holden, “Feasibility study of using yolov8 for cataract surgical tool detection in surgical microscope video.” Imaging Network Ontario, 2024. [ bib ]
[5] B. Long, Y. Guan, and M. S. Holden, “Improving model adaptability: A domain knowledge-integrated deep learning approach for ultrasound image segmentation and classification.” Imaging Network Ontario, 2024. [ bib ]
[6] J. Ruzicki, M. S. Holden, S. Cheon, T. Ungi, R. Egan, and C. Law, “Use of machine learning to assess cataract surgery skill level with tool detection,” Ophthalmology Science, vol. 3, no. 1, p. 100235, 2023. [ bib | DOI | .pdf ]
[7] K. Barr, L. Hookey, T. Ungi, G. Fichtinger, and M. S. Holden, “Analyzing colonoscopy training learning curves using comparative hand tracking assessment,” in Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 12466, pp. 466-472, SPIE, 2023. [ bib | DOI | .pdf ]
[8] D. Kulik, C. R. Bell, and M. S. Holden, “Fast skill assessment from kinematics data using convolutional neural networks,” International Journal of Computer Assisted Radiology and Surgery, pp. 1-7, 2023. [ bib | DOI | .pdf ]
[9] I. Gofman and M. S. Holden, “Classifying points of interest in fast ultrasound videos using neural networks.” Imaging Network Ontario, 2023. [ bib | .pdf ]
[10] J. Hsu, I. Churchill, M. S. Holden, and H. Lesiuk, “Prediction of cerebral vasospasm using radiographical and clinical features: a machine learning model.” Canadian Neurological Sciences Federation Congress, 2023. [ bib | .pdf ]
[11] B. Long, Y. Guan, and M. S. Holden, “A two-stage neural network model for breast ultrasound image classification,” in IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE), pp. 129-133, IEEE Computer Society, 2023. [ bib | DOI | .pdf ]
[12] R. Prager, P. Pageau, T. Hodges, C. Yan, M. Woo, M.-J. Nemnom, S. Millington, M. S. Holden, R. St-Gelais, and W. J. Cheung, “Characterizing the biomechanical differences between novice and expert point-of-care ultrasound practitioners using a low-cost gyroscope and accelerometer integrated sensor: A pilot study,” AEM Education and Training, vol. 6, no. 2, p. e10733, 2022. [ bib | DOI | .pdf ]
[13] O. O'Driscoll, R. Hisey, M. S. Holden, D. Camire, J. Erb, D. Howes, T. Ungi, and G. Fichtinger, “Feasibility of object detection for skill assessment in central venous catheterization,” in Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 12034, pp. 358-365, SPIE, 2022. [ bib | DOI | .pdf ]
[14] R. W. Chan, R. Hisey, and M. S. Holden, “Feasibility of video-based skills assessment: a study on ultrasound-guided needle insertions using simulated projections,” in Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 12034, pp. 663-669, SPIE, 2022. [ bib | DOI | .pdf ]
[15] H. Lee, R. Hisey, M. S. Holden, J. Liu, T. Ungi, G. Fichtinger, and C. Law, “Evaluating faster r-cnn for cataract surgery tool detection using microscopy video.” Imaging Network Ontario, 2022. [ bib | .pdf ]
[16] O. O'Driscoll, R. Hisey, M. S. Holden, D. Camire, J. Erb, D. Howes, T. Ungi, and G. Fichtinger, “Feasibility of using object detection for performance assessment in central venous catherization.” Imaging Network Ontario, 2022. [ bib | .pdf ]
[17] K. Yuan, M. S. Holden, S. Gao, and W. Lee, “Anticipation for surgical workflow through instrument interaction and recognized signals,” Medical Image Analysis, vol. 82, p. 102611, 2022. [ bib | DOI | .pdf ]
[18] A. N. Tasca, S. Carlucci, J. C. Wiley, M. S. Holden, A. El-Roby, and G. A. Tasca, “Detecting defense mechanisms from adult attachment interview (aai) transcripts using machine learning,” Psychotherapy Research, pp. 1-11, 2022. [ bib | DOI | .pdf ]
[19] K. Yuan, M. S. Holden, S. Gao, and W.-S. Lee, “Surgical workflow anticipation using instrument interaction,” in International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 615-625, Springer, 2021. [ bib | DOI | .pdf ]
[20] M. S. Holden, A. Portillo, and G. Salame, “Skills classification in cardiac ultrasound with temporal convolution and domain knowledge using a low-cost probe tracker,” Ultrasound in Medicine & Biology, vol. 47, no. 10, pp. 3002-3013, 2021. [ bib | DOI | .pdf ]
[21] M. S. Holden, M. O’Brien, A. Malpani, H. Naz, Y.-W. Tseng, L. Ishii, S. S. Vedula, M. Ishii, and G. Hager, “Reconstructing the nasal septum from instrument motion during septoplasty surgery,” Journal of Medical Imaging, vol. 8, no. 6, p. 065001, 2021. [ bib | DOI | .pdf ]
[22] T. Ungi, M. S. Holden, B. Zevin, and G. Fichtinger, “Chapter 37 - interventional procedures training,” in Handbook of Medical Image Computing and Computer Assisted Intervention (S. K. Zhou, D. Rueckert, and G. Fichtinger, eds.), pp. 909 - 929, Academic Press, 2020. [ bib | DOI ]
[23] J. Ruzicki, M. S. Holden, S. Cheon, T. Ungi, R. Egan, and C. Law, “Assessing cataract surgery skills through machine learning: A pilot study.” American Society of Cataract and Refractive Surgery Conference, 2020. [ bib | .pdf ]
[24] R. Liu and M. S. Holden, “Kinematics data representations for skills assessment in ultrasound-guided needle insertion,” in Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis, pp. 189-198, Springer, 2020. [ bib | DOI | .pdf ]
[25] R. E. Tyrrell and M. S. Holden, “Ultrasound video analysis for skill level assessment in fast ultrasound,” in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol. 0, pp. 1-5, Taylor & Francis, 2020. [ bib | DOI | .pdf ]
[26] J. Ruzicki, M. S. Holden, S. Cheon, T. Ungi, R. Egan, and C. Law, “Assessing cataract surgery skills through machine learning: A pilot study.” Canadian Ophthalmological Society, 2020. [ bib | .pdf ]
[27] R. McGraw, Z. Keri, T. Chaplin, L. Rang, M. Jaeger, N. Rocca, M. S. Holden, Z. Keri, and G. Fichtinger, “Cognitive load theory as a framework for simulation-based, ultrasound-guided internal jugular catheterization training: Once is not enough,” Canadian Journal of Emergency Medicine, vol. 21, no. 1, pp. 141-148, 2019. [ bib | DOI ]
[28] C. Yeo, J. Ring, M. S. Holden, T. Ungi, A. Toprak, G. Fichtinger, and B. Zevin, “Surgery tutor for computational assessment of technical proficiency in soft-tissue tumor resection in a simulated setting,” Journal of surgical education, vol. 76, no. 3, pp. 872-880, 2019. [ bib | DOI ]
[29] M. S. Holden, Computer-assisted Assessment and Feedback for Image-guided Interventions Training. PhD thesis, Queen's University, 2019. [ bib ]
[30] J. Laframboise, T. Ungi, L. Hookey, A. Lasso, M. Asselin, M. S. Holden, and G. Fichtinger, “Analyzing the curvature of the colon in different patient positions,” in Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10951, p. 109512F, International Society for Optics and Photonics, 2019. [ bib | DOI ]
[31] M. S. Holden, S. Xia, H. Lia, Z. Keri, C. Bell, L. Patterson, T. Ungi, and G. Fichtinger, “Machine learning methods for automated technical skills assessment with instructional feedback in ultrasound-guided interventions,” International Journal of Computer Assisted Radiology and Surgery, pp. 1-11, 2019. [ bib | DOI ]
[32] C. R. Bell and M. S. Holden, “Wanted: Automated objective proficiency assessment metrics for the fast exam (and other pocus studies),” European Journal of Trauma and Emergency Surgery, pp. 1-2, 2019. Letter to the Editor. [ bib | DOI ]
[33] S. Pasricha, Z. Keri, M. S. Holden, and G. Fichtinger, “Developing a simulation curriculum to teach medical students to perform an ultrasound-guided needle insertion.” Canadian Conference on Medical Education, 2019. [ bib ]
[34] J. Laframboise, T. Ungi, A. Lasso, M. Asselin, M. S. Holden, P. Tan, L. Hookey, and G. Fichtinger, “Quantifying the effect of patient position on the curvature of colons.” Imaging Network Ontario, 2019. [ bib ]
[35] P. Tan, J. Laframboise, C. Scott, R. Bechara, A. Lasso, M. Asselin, M. S. Holden, T. Ungi, and G. Fichtinger, “Quantitative assessment to determine change in colonic curvature with supine versus prone patient position using computed tomography colonography.” Canadian Digestive Diseases Week, 2019. [ bib ]
[36] M. S. Holden, C. N. Wang, K. MacNeil, B. Church, L. Hookey, G. Fichtinger, and T. Ungi, “Objective assessment of colonoscope manipulation skills in colonoscopy training,” International Journal of Computer Assisted Radiology and Surgery, vol. 13, no. 1, pp. 105-114, 2018. [ bib | DOI ]
[37] R. Leung, A. Lasso, M. S. Holden, B. Zevin, and G. Fichtinger, “Exploration using holographic hands as a modality for skills training in medicine,” in Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10576, p. 1057611, International Society for Optics and Photonics, 2018. [ bib | DOI ]
[38] S. Xia, Z. Keri, M. S. Holden, R. Hisey, H. Lia, T. Ungi, C. H. Mitchell, and G. Fichtinger, “A learning curve analysis of ultrasound-guided in-plane and out-of-plane vascular access training with perk tutor,” in Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10576, p. 1057625, International Society for Optics and Photonics, 2018. [ bib | DOI ]
[39] E. Rae, A. Lasso, M. S. Holden, E. Morin, R. Levy, and G. Fichtinger, “Neurosurgical burr hole placement using the microsoft hololens,” in Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10576, p. 105760T, International Society for Optics and Photonics, 2018. [ bib | DOI ]
[40] R. Hisey, T. Ungi, M. S. Holden, Z. Baum, Z. Keri, C. McCallum, D. W. Howes, and G. Fichtinger, “Real-time workflow detection using webcam video for providing real-time feedback in central venous catheterization training,” in Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10576, p. 1057620, International Society for Optics and Photonics, 2018. Honorable mention poster award. [ bib | DOI ]
[41] M. S. Holden, Y. Zhao, C. Haegelen, C. Essert, S. Fernandez-Vidal, E. Bardinet, T. Ungi, G. Fichtinger, and P. Jannin, “Self-guided training for deep brain stimulation planning using objective assessment,” International Journal of Computer Assisted Radiology and Surgery, vol. 13, no. 7, pp. 1129-1139, 2018. [ bib | DOI ]
[42] M. S. Holden, H. Lia, S. Xia, Z. Keri, T. Ungi, and G. Fichtinger, “Configurable overall skill assessment in ultrasound-guided needle insertion.” Imaging Network Ontario, 2018. [ bib ]
[43] D. Garcia-Mato, M. S. Holden, A. Lasso, A. Szulewski, J. Pascau, and G. Fichtinger, “3d gaze tracking for skill assessment in ultrasound-guided needle insertions,” in 32nd International Congress and Exhibition of Computer Assisted Radiology and Surgery, vol. Supplement 1, pp. S52-S53, 2018. [ bib | DOI ]
[44] S. Pasricha, Z. Keri, M. S. Holden, and G. Fichtinger, “Developing a simulation curriculum to teach medical students to perform an ultrasound-guided needle insertion.” William Ersil Resident Research Day, Best non-resident orthopaedic paper, 2018. [ bib ]
[45] J. Ring, C. T. Yeo, M. S. Holden, T. Ungi, G. Fichtinger, and B. Zevin, “Surgery tutor for assessment of technical proficiency in open soft-tissue tumour resection: A validation study.” International Conference on Residency Education, 2018. [ bib ]
[46] C. T. Yeo, J. Ring, M. S. Holden, T. Ungi, G. Fichtinger, and B. Zevin, “Validation of surgery tutor for assessment of technical proficiency in soft-tissue tumour resection.” Canadian Surgery Forum, 2018. [ bib ]
[47] S. Xia, Z. Keri, M. S. Holden, R. Hisey, H. Lia, T. Ungi, L. Patterson, and G. Fichtinger, “Ultrasound-guided vascular access training with 3d visualization guidance in novice medical trainees.” Canadian Anesthesiologists’ Annual Meeting, Best Paper in Education and Simulation Finalist, 2018. [ bib ]
[48] E. Rae, A. Lasso, M. S. Holden, E. Morin, R. Levy, and G. Fichtinger, “Accuracy of the microsoft hololens for neurosurgical burr hole placement.” Imaging Network Ontario, 2018. [ bib ]
[49] R. Hisey, T. Ungi, M. S. Holden, Z. Baum, Z. Keri, C. McCallum, D. W. Howes, and G. Fichtinger, “Assessment of the use of webcam based workflow detection for providing real-time feedback in central venous catheterization training.” Imaging Network Ontario, 2018. [ bib ]
[50] R. Leung, A. Lasso, M. S. Holden, B. Zevin, and G. Fichtinger, “Using augmented-reality for self-directed surgical skills training in competency-based medical education.” Imaging Network Ontario, 2018. [ bib ]
[51] S. Xia, Z. Keri, M. S. Holden, R. Hisey, H. Lia, T. Ungi, and G. Fichtinger, “Ultrasound-guided needle insertion simulator with tracking- and video-based skill assessment.” Imaging Network Ontario, 2018. [ bib ]
[52] C. T. Yeo, J. Ring, M. S. Holden, T. Ungi, G. Fichtinger, and B. Zevin, “Surgery tutor – an open source platform for assessment of technical proficiency: A validation study in a simulated setting.” American College of Surgeons Surgical Simulation Summit, 2018. [ bib ]
[53] C. R. Bell, C. McKaigney, M. S. Holden, G. Fichtinger, and L. Rang, “Sonographic accuracy as a novel tool for point-of-care ultrasound competency assessment,” AEM Education and Training, vol. 1, no. 4, pp. 316-324, 2017. [ bib | DOI ]
[54] M. S. Holden, Z. Keri, T. Ungi, and G. Fichtinger, “Overall proficiency assessment in point-of-care ultrasound interventions: The stopwatch is not enough,” in Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound, pp. 146-153, Springer, 2017. [ bib | DOI ]
[55] H. Lia, Z. Keri, M. S. Holden, V. Harish, C. H. Mitchell, T. Ungi, and G. Fichtinger, “Training with perk tutor improves ultrasound-guided in-plane needle insertion skill,” in Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10135, p. 101350T, International Society for Optics and Photonics, 2017. [ bib | DOI ]
[56] V. Harish, E. Bibic, A. Lasso, M. S. Holden, T. Vaughan, Z. Baum, T. Ungi, and G. Fichtinger, “Monitoring electromagnetic tracking error using redundant sensors,” in Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10135, p. 101352R, International Society for Optics and Photonics, 2017. [ bib | DOI ]
[57] C. N. Wang, M. S. Holden, T. Ungi, G. Fichtinger, C. M. Walsh, and L. Hookey, “Developing a competency-based performance metric of colonoscopy skills acquisition using motion analysis - step 1: Low-fidelity benchtop model.” Journal of the Canadian Association of Gastroenterology, 2017. [ bib ]
[58] R. Leung, A. Lasso, M. S. Holden, G. Fichtinger, and B. Zevin, “Exploration using holographic hands as a modality for skills training in medicine.” Artificial Intelligence in Medicine, Best Abstract Award in Digital Medicine and Wearable Technology, 2017. [ bib ]
[59] R. McGraw, Z. Keri, N. Rocca, T. Chaplin, L. Rang, M. Jaeger, M. S. Holden, and G. Fichtinger, “Using cognitive load theory to guide simulation-based ultrasound-guided internal jugular catheterization training: Once is not enough.” Royal College of Physicians and Surgeons of Canada Simulation Summit, 2017. [ bib ]
[60] Z. Keri, T. Ungi, M. S. Holden, G. Fichtinger, and R. McGraw, “Computer-assisted training and evaluation in procedural skill acquisition.” Annual Meeting for Health Sciences Research Trainees, 2017. [ bib ]
[61] M. S. Holden, C. N. Wang, K. MacNeil, B. Church, L. Hookey, G. Fichtinger, and T. Ungi, “Assessing technical competence in simulated colonoscopy using joint motion analysis.” Queen’s Graduate Computing Society Conference, Runner-up poster award, 2017. [ bib ]
[62] M. S. Holden, C. N. Wang, K. MacNeil, B. Church, L. Hookey, G. Fichtinger, and T. Ungi, “Assessing technical competence in simulated colonoscopy using joint motion analysis.” Imaging Network Ontario, 2017. [ bib ]
[63] V. Harish, E. Bibic, A. Lasso, M. S. Holden, T. Vaughan, Z. Baum, T. Ungi, and G. Fichtinger, “An application of redundant sensors for intraoperative electromagnetic tracking error monitoring.” Imaging Network Ontario, 2017. [ bib ]
[64] K. Carter, T. Vaughan, M. S. Holden, G. Gauvin, P. Pezeshki, A. Lasso, T. Ungi, E. Morin, J. Rudan, J. Engel, and G. Fichtinger, “Visual feedback mounted on surgical tool: Proof of concept,” in Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 9786, p. 978614, International Society for Optics and Photonics, 2016. [ bib | DOI ]
[65] M. Woodcroft, T. Chaplin, L. Rang, M. Jaeger, M. S. Holden, N. Rocca, T. Ungi, G. Fichtinger, and R. McGraw, “Development of a simulation-based curriculum for ultrasound-guided internal jugular central venous catheterization.” Canadian Journal of Emergency Medicine, 2016. [ bib ]
[66] R. McGraw, T. Chaplin, C. McKaigney, L. Rang, M. Jaeger, D. Redfearn, C. Davison, T. Ungi, M. S. Holden, C. Yeo, Z. Keri, and G. Fichtinger, “Development and evaluation of a simulation-based curriculum for ultrasound-guided central venous catheterization,” Canadian Journal of Emergency Medicine, vol. 18, no. 6, pp. 405-413, 2016. [ bib | DOI ]
[67] M. Woodcroft, T. Chaplin, L. Rang, M. Jaeger, M. S. Holden, N. Rocca, T. Ungi, G. Fichtinger, and R. McGraw, “Development of a simulation-based curriculum for ultrasound-guided internal jugular central venous catheterization.” Annual Meeting for Health Sciences Research Trainees, 2016. [ bib ]
[68] M. S. Holden, M. Woodcroft, T. Chaplin, L. Rang, M. Jaeger, N. Rocca, R. C. McGraw, G. Fichtinger, and T. Ungi, “Central venous catheterization curriculum development via objective performance metrics.” Imaging Network Ontario, Cum Laude Award, 2016. [ bib ]
[69] K. MacNeil, C. Wang, M. S. Holden, T. Ungi, G. Fichtinger, and L. Hookey, “System for objectively evaluating colonoscopy procedural skills using motion analysis.” Imaging Network Ontario, 2016. [ bib ]
[70] R. McGraw, T. Chaplin, C. McKaigney, L. Rang, M. Jaeger, D. Redfearn, C. Davison, T. Ungi, M. S. Holden, C. Yeo, Z. Keri, G. Fichtinger, M. Woodcroft, and N. Rocca, “Using hand motion analysis to establish learning curves in ultrasound guided central venous access.” CAEP Feature Education Innovations, 2016. [ bib ]
[71] D. Clinkard, E. Moult, M. S. Holden, C. Davison, T. Ungi, G. Fichtinger, and R. C. McGraw, “Assessment of lumbar puncture skill in experts and nonexperts using checklists and quantitative tracking of needle trajectories: Implications for competency-based medical education,” Teaching and learning in medicine, vol. 27, no. 1, pp. 51-56, 2015. [ bib | DOI ]
[72] D. Clinkard, M. S. Holden, T. Ungi, C. Davison, D. Messenger, G. Fichtinger, and R. McGraw, “The development and validation of hand motion analysis to evaluate competency in central line catheterization,” Academic Emergency Medicine, vol. 22, no. 2, pp. 212-218, 2015. [ bib | DOI ]
[73] Z. Keri, D. Sydor, T. Ungi, M. S. Holden, P. Mousavi, R. McGraw, D. Borschneck, G. Fichtinger, and M. Jaeger, “Computerized training system for ultrasound-guided lumbar puncture on abnormal spine models: A randomized controlled trial,” Canadian Journal of Anesthesia/Journal canadien d'anesthésie, vol. 62, no. 7, pp. 777-784, 2015. [ bib | DOI ]
[74] C. Yeo, C. Davison, T. Ungi, M. S. Holden, G. Fichtinger, and R. McGraw, “Examination of learning trajectories for simulated lumbar puncture training using hand motion analysis,” Academic Emergency Medicine, vol. 22, no. 10, pp. 1187-1195, 2015. [ bib | DOI ]
[75] M. S. Holden, T. Ungi, C. McKaigney, C. Bell, L. Rang, and G. Fichtinger, “Objective evaluation of sonographic skill in focussed assessment with sonography for trauma examinations,” in 29th International Congress and Exhibition of Computer Assisted Radiology and Surgery, vol. Supplement 1, pp. S79-S80, 2015. [ bib | DOI ]
[76] M. Soehl, M. S. Holden, A. Lasso, and G. Fichtinger, “Scalable ultrasound calibration phantoms made from lego® bricks,” in 29th International Congress and Exhibition of Computer Assisted Radiology and Surgery, vol. Supplement 1, pp. S218-S219, 2015. [ bib | DOI ]
[77] M. Woodcroft, T. Chaplin, L. Rang, M. Jaeger, M. S. Holden, N. Rocca, T. Ungi, G. Fichtinger, and R. McGraw, “Development of a simulation-based curriculum for ultrasound-guided internal jugular central venous catheterization.” Queen’s University Medical Student Research Showcase, 2015. [ bib ]
[78] C. Bell, C. McKaigney, M. S. Holden, J. Newbigging, T. Ungi, G. Fichtinger, and L. Rang, “Ultrasound probe motion tracking as a novel tool for pocus competency assessment.” Canadian Association of Emergency Physicians, 2015. [ bib ]
[79] M. S. Holden, T. Ungi, D. Sargent, R. C. McGraw, E. C. S. Chen, S. Ganapathy, T. M. Peters, and G. Fichtinger, “Feasibility of real-time workflow segmentation for tracked needle interventions,” IEEE Transactions on Biomedical Engineering, vol. 61, no. 6, pp. 1720-1728, 2014. [ bib | DOI ]
[80] T. Ungi, D. Beiko, M. Fuoco, F. King, M. S. Holden, G. Fichtinger, and R. Siemens, “Tracked ultrasonography snapshots enhance needle guidance for percutaneous renal access: A pilot study,” Journal of Endourology, vol. 28, no. 9, pp. 1040-1045, 2014. [ bib | DOI ]
[81] M. S. Holden, “Linear object registration for image-guided interventions,” Master's thesis, Queen's University, 2014. [ bib ]
[82] M. S. Holden and G. Fichtinger, “Linear object registration of interventional tools,” in Workshop on Augmented Environments for Computer-Assisted Interventions, pp. 118-127, Springer, 2014. [ bib | DOI ]
[83] D. Clinkard, M. S. Holden, D. Messenger, T. Ungi, C. Davidson, G. Fichtinger, and R. McGraw, “Quantifying competency – the development and validation of a hand motion analysis program to discriminate experts and non-experts during central venous line cannulation.” Canadian Anesthesiology Society, 2014. [ bib ]
[84] M. S. Holden and G. Fichtinger, “Linear object registration: A registration algorithm using points, lines, and planes.” Queen’s University Graduate Computing Society Conference, 2014. [ bib ]
[85] D. Clinkard, M. S. Holden, D. Messenger, T. Ungi, C. Davidson, G. Fichtinger, and R. McGraw, “Quantifying competency – the development and validation of a hand motion analysis program to discriminate experts and non-experts during central venous line cannulation.” Canadian Association of Emergency Physicians, 2014. [ bib ]
[86] M. S. Holden and G. Fichtinger, “Linear object registration: A registration algorithm using points, lines, and planes.” Imaging Network Ontario, 2014. [ bib ]
[87] T. Ungi, D. Beiko, M. Fuoco, F. King, M. S. Holden, R. Siemens, and G. Fichtinger, “Tracked ultrasound snapshots improve the performance of novices in simulated nephrostomy.” Imaging Network Ontario, 3rd place poster award, 2014. [ bib ]
[88] Z. Keri, D. Sydor, T. Ungi, M. S. Holden, R. McGraw, D. Borschneck, M. Jaeger, and G. Fichtinger, “A novel technology for teaching ultrasound-guided intrathecal needle insertion with perk tutor.” Imaging Network Ontario, 2014. [ bib ]
[89] D. Clinkard, E. Moult, M. S. Holden, G. Fichtinger, T. Ungi, and R. C. McGraw, “The validity of hand and tool motion analysis as an observer independent method of assessing competency – implications for assessment in competency-based education.” Queen’s University Medical Student Research Showcase, 2013. [ bib ]
[90] M. S. Holden, T. Ungi, D. Sargent, R. C. McGraw, E. C. S. Chen, S. Ganapathy, T. M. Peters, and G. Fichtinger, “Real-time workflow segmentation for needle-based interventions.” Imaging Network Ontario, 3rd place poster award, 2013. [ bib ]
[91] M. S. Holden, T. Ungi, D. Sargent, R. C. McGraw, and G. Fichtinger, “Surgical motion characterization in simulated needle insertion procedures,” in Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 8316, p. 83160W, International Society for Optics and Photonics, 2012. [ bib | DOI ]
[92] M. S. Holden, D. G. C. McKeon, and T. N. Sherry, “The double slit experiment with polarizers,” Canadian Journal of Physics, vol. 89, no. 11, pp. 1079-1081, 2011. [ bib | DOI ]
[93] M. S. Holden, “Clearcut regions and the multi-valued nature of the complex logarithm.” Canadian Undergraduate Mathematics Conference, 2011. [ bib ]
[94] M. S. Holden, G. Fichtinger, C. Haegelen, P. Jannin, and Y. Zhao, “Proficiency assessment system and method for deep brain stimulation (dbs),” filed 2017. [ bib ]