[1] H. Rivaz and D. L. Collins, “Near real-time robust non-rigid registration of volumetric ultrasound images for neurosurgery,” Ultrasound in medicine & biology, vol. 41, no. 2, pp. 574–587, 2015.
[2] D. Fontanarosa, S. van der Meer, J. Bamber, E. Harris, T. O?Shea, and F. Verhaegen, “Review of ultrasound image guidance in external beam radiotherapy: I. treatment plan- ning and inter-fraction motion management,” Physics in medicine and biology, vol. 60, no. 3, p. R77, 2015.
[3] J. A. Schnabel, M. P. Heinrich, B. W. Papiez ̇, and J. M. Brady, “Advances and challenges in deformable image registration: From image fusion to complex motion modelling,” Medical Image Analysis, 2016.
[4] J.-P. Thirion, “Image matching as a diffusion process: an analogy with maxwell’s demons,” Medical image analysis, vol. 2, no. 3, pp. 243–260, 1998.
[5] D. Rueckert, L. I. Sonoda, C. Hayes, D. L. Hill, M. O. Leach, and D. J. Hawkes, “Non- rigid registration using free-form deformations: application to breast mr images,” IEEE transactions on medical imaging, vol. 18, no. 8, pp. 712–721, 1999.
[6] M. A. Viergever, J. A. Maintz, S. Klein, K. Murphy, M. Staring, and J. P. Pluim, “A survey of medical image registration–under review,” Medical Image Analysis, 2016.
[7] G. E. Christensen and H. J. Johnson, “Consistent image registration,” IEEE Transactions on Medical Imaging, vol. 20, no. 7, pp. 568–582, 2001.
[8] D. Shen and C. Davatzikos, “Hammer: hierarchical attribute matching mechanism for elastic registration,” IEEE Transactions on Medical Imaging, vol. 21, no. 11, pp. 1421– 1439, 2002.
[9] A. Sotiras, C. Davatzikos, and N. Paragios, “Deformable medical image registration: A survey,” Medical Imaging, IEEE Transactions on, vol. 32, no. 7, pp. 1153–1190, 2013.
[10] F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens, “Multimodal- ity image registration by maximization of mutual information,” IEEE Transactions on Medical Imaging, vol. 16, no. 2, pp. 187–198, 1997.
[11] P. Viola and W. M. Wells III, “Alignment by maximization of mutual information,” In- ternational journal of computer vision, vol. 24, no. 2, pp. 137–154, 1997.
[12] R. L. Siegel, K. D. Miller, and A. Jemal, “Cancer statistics, 2015,” CA: a cancer journal for clinicians, vol. 65, no. 1, pp. 5–29, 2015.
[13] M. Quinn and P. Babb, “Patterns and trends in prostate cancer incidence, survival, preva- lence and mortality. part i: international comparisons,” BJU international, vol. 90, no. 2, pp. 162–173, 2002.
[14] F. Petrelli, I. Vavassori, A. Coinu, K. Borgonovo, E. Sarti, and S. Barni, “Radical prosta- tectomy or radiotherapy in high-risk prostate cancer: a systematic review and metaanal- ysis,” Clinical genitourinary cancer, vol. 12, no. 4, pp. 215–224, 2014.
[15] K. Langen and D. Jones, “Organ motion and its management,” International Journal of Radiation Oncology* Biology* Physics, vol. 50, no. 1, pp. 265–278, 2001.
[16]M.R.Moman,U.A.vanderHeide,A.N.Kotte,R.J.A.vanMoorselaar,G.H.Bol,S.P. Franken, and M. van Vulpen, “Long-term experience with transrectal and transperineal implantations of fiducial gold markers in the prostate for position verification in external beam radiotherapy; feasibility, toxicity and quality of life,” Radiotherapy and Oncology, vol. 96, no. 1, pp. 38–42, 2010.
[17] W. Stummer, U. Pichlmeier, T. Meinel, O. D. Wiestler, F. Zanella, H.-J. Reulen, ALA- Glioma Study Group et al., “Fluorescence-guided surgery with 5-aminolevulinic acid for resection of malignant glioma: a randomised controlled multicentre phase iii trial,” The lancet oncology, vol. 7, no. 5, pp. 392–401, 2006.
[18] A. Nabavi, P. M. Black, D. T. Gering, C.-F. Westin, V. Mehta, R. S. Pergolizzi Jr, M. Fer- rant, S. K. Warfield, N. Hata, R. B. Schwartz et al., “Serial intraoperative magnetic resonance imaging of brain shift,” Neurosurgery, vol. 48, no. 4, pp. 787–798, 2001.
[19] G. Unsgård, O. Solheim, F. Lindseth, and T. Selbekk, Intra-operative imaging with 3D ultrasound in neurosurgery. Springer, 2011.
[20] O. Solheim, T. Selbekk, A. S. Jakola, and G. Unsgård, “Ultrasound-guided operations in unselected high-grade gliomas—overall results, impact of image quality and patient selection,” Acta neurochirurgica, vol. 152, no. 11, pp. 1873–1886, 2010.
[21] M. A. El Beltagy, M. Aggag, and M. Kamal, “Role of intraoperative ultrasound in resec- tion of pediatric brain tumors,” Child’s Nervous System, vol. 26, no. 9, pp. 1189–1193, 2010.
[22] M. Renovanz, A.-K. Hickmann, C. Henkel, M. Nadji-Ohl, and N. J. Hopf, “Navigated versus non-navigated intraoperative ultrasound: is there any impact on the extent of re- section of high-grade gliomas? a retrospective clinical analysis.” Journal of neurological surgery. Part A, Central European neurosurgery, vol. 75, no. 3, pp. 224–230, 2014.
[23] A. K. Petridis, M. Anokhin, J. Vavruska, M. Mahvash, and M. Scholz, “The value of intraoperative sonography in low grade glioma surgery,” Clinical neurology and neuro- surgery, vol. 131, pp. 64–68, 2015.
[24] J. Coburger, A. Scheuerle, D. R. Thal, J. Engelke, M. Hlavac, C. R. Wirtz, and R. König, “Linear array ultrasound in low-grade glioma surgery: histology-based assessment of ac- curacy in comparison to conventional intraoperative ultrasound and intraoperative mri,” Acta neurochirurgica, vol. 157, no. 2, pp. 195–206, 2015.
[25] A. V. Moiyadi and P. Shetty, “Direct navigated 3d ultrasound for resection of brain tu- mors: a useful tool for intraoperative image guidance,” Neurosurgical Focus, vol. 40, no. 3, p. E5, 2016.
[26] T. Selbekk, A. S. Jakola, O. Solheim, T. F. Johansen, F. Lindseth, I. Reinertsen, and G. Unsgård, “Ultrasound imaging in neurosurgery: approaches to minimize surgically induced image artefacts for improved resection control,” Acta neurochirurgica, vol. 155, no. 6, pp. 973–980, 2013.
[27] J. A. Zagzebski, “Essentials of ultrasound physics,” 1996.
[28] P. Foroughi, P. Abolmaesumi, and K. Hashtrudi-Zaad, “Intra-subject elastic registration
of 3d ultrasound images,” Medical image analysis, vol. 10, no. 5, pp. 713–725, 2006.
[29] R. J. Schneider, D. P. Perrin, N. V. Vasilyev, G. R. Marx, J. Pedro, and R. D. Howe, “Real-time image-based rigid registration of three-dimensional ultrasound,” Medical im- age analysis, vol. 16, no. 2, pp. 402–414, 2012.
[30] I. Reinertsen, F. Lindseth, C. Askeland, D. H. Iversen, and G. Unsgård, “Intra-operative correction of brain-shift,” Acta neurochirurgica, vol. 156, no. 7, pp. 1301–1310, 2014.
[31] V. Grau, H. Becher, and J. A. Noble, “Registration of multiview real-time 3-d echocar- diographic sequences,” IEEE Transactions on Medical Imaging, vol. 26, no. 9, pp. 1154– 1165, 2007.
[32] K. Rajpoot, J. A. Noble, V. Grau, C. Szmigielski, and H. Becher, “Multiview rt3d echocardiography image fusion,” in Functional Imaging and Modeling of the Heart. Springer, 2009, pp. 134–143.
[33] L. Mercier, D. Araujo, C. Haegelen, R. F. Del Maestro, K. Petrecca, and D. L. Collins, “Registering pre-and postresection 3-dimensional ultrasound for improved visualization of residual brain tumor,” Ultrasound in medicine & biology, vol. 39, no. 1, pp. 16–29, 2013.
[34] B. Presles, M. Fargier-Voiron, M.-C. Biston, R. Lynch, A. Munoz, H. Liebgott, P. Pom- mier, S. Rit, and D. Sarrut, “Semiautomatic registration of 3d transabdominal ultra- sound images for patient repositioning during postprostatectomy radiotherapy,” Medical physics, vol. 41, no. 12, p. 122903, 2014.
[35] T. O’Shea, J. Bamber, and E. Harris, “Mo-de-210-05: Improved accuracy of liver feature motion estimation in b-mode ultrasound for image-guided radiation therapy,” Medical physics, vol. 42, no. 6, pp. 3560–3560, 2015.
[36] J. Banerjee, C. Klink, E. D. Peters, W. J. Niessen, A. Moelker, and T. van Walsum, “Fast and robust 3d ultrasound registration–block and game theoretic matching,” Medical image analysis, vol. 20, no. 1, pp. 173–183, 2015.
[37] Y. Gao, J. Ma, J. Zhao, J. Tian, and D. Zhang, “A robust and outlier-adaptive method for non-rigid point registration,” Pattern Analysis and Applications, vol. 17, no. 2, pp. 379–388, 2014.
[38] A. Khamene, D. Zikic, M. Diallo, T. Boettger, and E. Rietzel, “A novel intensity simi- larity metric with soft spatial constraint for a deformable image registration problem in radiation therapy,” in Medical Image Computing and Computer-Assisted Intervention– MICCAI 2009. Springer, 2009, pp. 828–836.
[39] H. Zhou and H. Rivaz, “Registration of pre-and post-resection ultrasound volumes with non-corresponding regions in neurosurgery,” IEEE Journal of Biomedical and Health Informatics, vol. PP, no. 99, pp. 1–1, 2016.
[40] E. Malis, “Improving vision-based control using efficient second-order minimization techniques,” in ICRA’04. 2004 IEEE International Conference on Robotics and Automa- tion, vol. 2. IEEE, 2004, pp. 1843–1848.
[41] H. Zhou and H. Rivaz, “Robust deformable registration of pre-and post-resection ultra- sound volumes for visualization of residual tumor in neurosurgery,” in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. IEEE, 2015, pp. 141–144.
[42] M. P. Heinrich, M. Jenkinson, M. Bhushan, T. Matin, F. V. Gleeson, M. Brady, and J. A. Schnabel, “Mind: Modality independent neighbourhood descriptor for multi-modal deformable registration,” Medical Image Analysis, vol. 16, no. 7, pp. 1423–1435, 2012.
[43] M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Medical physics, vol. 35, no. 1, pp. 81–88, 2008.
[44] H. Rivaz, S. J.-S. Chen, and D. L. Collins, “Automatic deformable mr-ultrasound regis- tration for image-guided neurosurgery,” IEEE Transactions on Medical Imaging, vol. 34, no. 2, pp. 366–380, 2015.
[45] E. Malis, “Vision-based estimation and robot control,” Ph.D. dissertation, Université Nice Sophia Antipolis, 2008.
[46] L. Mercier, R. F. Del Maestro, K. Petrecca, D. Araujo, C. Haegelen, and D. L. Collins, “Online database of clinical mr and ultrasound images of brain tumors,” Medical physics, vol. 39, no. 6, pp. 3253–3261, 2012.
[47] P. Jannin, J. M. Fitzpatrick, D. Hawkes, X. Pennec, R. Shahidi, and M. Vannier, “Val- idation of medical image processing in image-guided therapy.” IEEE Transactions on Medical Imaging, vol. 21, no. 12, pp. 1445–1449, 2002.
[48] M. Van Herk, “Errors and margins in radiotherapy,” in Seminars in radiation oncology, vol. 14, no. 1. Elsevier, 2004, pp. 52–64.
[49]H.A.McNair,V.N.Hansen,C.C.Parker,P.M.Evans,A.Norman,E.Miles,E.J.Harris, L. Del-Acroix, E. Smith, R. Keane et al., “A comparison of the use of bony anatomy and internal markers for offline verification and an evaluation of the potential benefit of online and offline verification protocols for prostate radiotherapy,” International Journal of Radiation Oncology* Biology* Physics, vol. 71, no. 1, pp. 41–50, 2008.
[50] M. Lachaine and T. Falco, “Intrafractional prostate motion management with the clarity autoscan system,” Med. Phys. Int, vol. 1, no. 1, pp. 72–80, 2013.
[51] J. A. Molloy, G. Chan, A. Markovic, S. McNeeley, D. Pfeiffer, B. Salter, and W. A. Tome, “Quality assurance of us-guided external beam radiotherapy for prostate cancer: Report of aapm task group 154,” Medical physics, vol. 38, no. 2, pp. 857–871, 2011.
[52] M. Fargier-Voiron, B. Presles, P. Pommier, A. Munoz, S. Rit, D. Sarrut, and M.-C. Biston, “Evaluation of a new transperineal ultrasound probe for inter-fraction image- guidance for definitive and post-operative prostate cancer radiotherapy,” Physica Med- ica, vol. 32, no. 3, pp. 499–505, 2016.