| |
Awards Won by Students Under Thesis Supervision and Post-Doctoral Fellows
|
|
Sobhan Goudarzi ranked First (tied) in Challenge on Ultrasound Beamforming with Deep Learning (CUBDL).
Nima Masoumi received the MASc Convocation Award in recognition of the best MASc thesis in the ECE Department in 2019. ECE is home to ~150 thesis-based MASc students.
Hoda Hashemi received the MASc Convocation Award in recognition of the best MASc thesis in the ECE Department in 2018. ECE is home to ~150 thesis-based MASc students.
(Hashemi & Rivaz IEEE TUFFC 2017) among Editor's Selection of Articles in TUFFC (Dec 2018).
Dr. Yiming Xiao received the BrainsCAN postdoctoral scholarship. $110,000 over 2 years. 2018.
(Shams*, Boily, Martineau, Rivaz, SPIE 2016, San Diego, CA) selected as a finalist for the Robert F. Wagner All Conference Best Student Paper Award. Only 16 finalists among more than 1000 presentations. Paper presented by R Shams, MASc student.
(Zhou* & Rivaz, IEEE EMBC, Milan, Italy) invited for submission of full journal version. Only 10 invitations among 2948 submissions to IEEE EMBC. Paper presented by MASc student H Zhou. The IEEE JBHI paper (Zhou* & Rivaz 2016) is now published.
H. Khodadadi*, Best poster award, 3rd Annual PERFORM Conference. Sponsored by Biospective. $500. 2016
R. Shams*, Second place award in Graduate Student Research paper competition, MASc category. $300. 2016
R. Shams*, First place award in Graduate Student Research paper competition, MASc category. $300. 2015
|
Selected Awards
|
|
Concordia University Research Chair in Medical Image Analysis (New Scholar), 2018
Petro-Canada Young Innovator Award, 2016
NSERC Post-Doctoral Fellowship, 2012-2013 ($80,000 CAD)
Jeanne Timmins Costello Post-Doctoral Award, 2011, 2014 ($80,000 CAD)
DoD Pre-Doctoral Traineeship Award, 2008-2011 ($97,000 USD)
Advanced Simulation Fellowship from the Link Foundation, 2008 ($25,000 USD)
STACOM best paper award, 2012 ($400)
MICCAI travel award, 2009 ($700)
SPIE Medical Imaging second best paper award, 2009
UBC Graduate Entrance award and partial tuition Remission award, 2003
University of Toronto Connaught Scholarship (declined), 2003
Ranked 2 among >15,000, Iranian national university entrance exam for graduate studies, 2003
Ranked 5 among > 150,000, Iranian national university entrance exam for undergraduate studies, 1999
Silver medal, 12th National Physics Olympiad, 1998
|
Selected Publications (Asterisk * indicates students under supervision)
See all publications on Google Scholar
|
|
[Disclaimer: Posting of copies of papers is intended for
educational purposes only and adherence to copyright laws is assumed.]
|
2020:
|
|
Journal Papers: |
 |
104. S. Goudarzi*, A. Asif, and H. Rivaz,
Fast Multi-Focus Ultrasound Image Recovery Using Generative Adversarial Networks, IEEE Trans. Comput. Imag. (TCI), 2020, pp 1272-1284
pdf , supplementary material, IEEE Xplore.
|
 |
103. M. Amiri*, R. Brooks, H. Rivaz,
Fine-tuning U-Net for ultrasound image segmentation: different layers, different outcomes,
IEEE Trans. UFFC (TUFFC), Special Issue on Deep Learning, in press
pdf , supplementary material
|
 |
102. M. Amiri*, R. Brooks, B. Behboodi*, H. Rivaz,
Two-stage ultrasound image segmentation using U-Net and test time augmentation,
Springer IJCARS, in press
pdf.
|
 |
101. A. Tehrani*, H. Rivaz,
Displacement Estimation in Ultrasound Elastography using Pyramidal Convolutional Neural Network,
IEEE Trans. UFFC (TUFFC), Special Issue on Deep Learning, in press
pdf, supplementary material, code, data.
|
 |
100. M. Sharifzadeh*, H. Benali, H. Rivaz,
Phase aberration correction: a convolutional neural network approach,
IEEE Access, in press
Full paper.
|
 |
99. A. Zayed*, H. Rivaz,
Fast Strain Estimation and Frame Selection in Ultrasound Elastography using Machine Learning,
IEEE Trans. UFFC (TUFFC), in press
pdf, supplementary material, code.
|
 |
98. M. Aktar*, D. Tampieri, H. Rivaz, M. Kersten-Oertel, Y. Xiao,
Automatic Collateral Circulation Scoring in Ischemic Stroke using 4D CT Angiography with Low-Rank and Sparse Matrix Decomposition,
Springer IJCARS, in press, pdf.
|
 |
97. N. Zhang*, M. Ashikuzzaman*, H. Rivaz,
Clutter Suppression in Ultrasound: Performance Evaluation and Review of Low-Rank and Sparse Matrix Decomposition Methods, Springer Biomedical Engineering Online, in press
pdf.
|
 |
96. M. Mirzaei*, A. Asif, M. Fortin, H. Rivaz,
Accurate and Precise Time-Delay Estimation for Ultrasound Elastography with Pre-Beamformed Channel Data,
IEEE Trans. UFFC (TUFFC), in press
pdf, code.
|
 |
95. A. Roy, H. Rivaz, A Rizk, S Frenette, M Boily, M Fortin,
Seasonal Changes in Lumbar Multifidus Muscle in University Rugby Players,
Medicine & Science in Sports & Exercise, in press
pdf.
|
 |
94. A. Grimwood, H. Rivaz, H Zhou, H McNair, K Yakubowski, J Bamber, A Tree, E Harris,
Improving 3D ultrasound prostate localisation in radiotherapy through increased automation of interfraction matching,
Radiotherapy and Oncology, in press
pdf, Elsevier.
|
|
93. N Nandlall, H. Rivaz, A Rizk, S Frenette, M Boily, M Fortin
The effect of low back pain and lower limb injury on lumbar multifidus muscle morphology and function in university soccer players, BMC Musculoskeletal Disorders, in press,
pdf.
|
 |
92. M Ashikuzzaman*, C Belasso*, G Kibria*, A Bergdahl, C Gauthier, H. Rivaz,
Low Rank and Sparse Decomposition of Ultrasound Color Flow Images for Suppressing Clutter in Real-Time,
IEEE Trans. Medical Imaging (TMI), in press
IEEE Xplore, pdf, supplementary material, code.
|
 |
91. A Schyver, H Rivaz, A Rizk, S Frenette, M Boily, M Fortin
Ultrasonography of Lumbar Multifidus Muscle in University American Football Players, Medicine and science in sports and exercise, in press,
PubMed, pdf.
|
 |
90. M. Mirzaei*, A. Asif, M. Fortin, H. Rivaz,
3D normalized cross-correlation for estimation of the displacement field in ultrasound elastography,
Ultrasonics, in press
ScienceDirect, pdf, supplementary material, code.
|
 |
89. J Levesque, H. Rivaz, A Rizk, S Frenette, M Boily, M Fortin
Associations among lumbar multifidus muscle characteristics, body composition and injury in university rugby players, Journal of Athletic Training, in press,
pdf.
|
 |
88. Y Xiao, H. Rivaz, M Chabanas, M Fortin, I Machado, Y Ou, M Heinrich, J Schnabel, X Zhong,
A Maier, W Wein, R Shams, S Kadoury, D Drobny, M Modat, I Reinertsen, Evaluation of MRI to ultrasound registration methods for brain shift correction: The CuRIOUS2018 Challenge,
IEEE Trans. Medical Imaging (TMI), vol 39, pp 777-786, 2020
IEEE Xplore, pdf.
|
| |
Conf. Papers: |
 |
87. A. Tehrani*, M. Mirzaei*, H. Rivaz,
Semi-Supervised Training of Optical Flow Convolutional Neural Networks in Ultrasound Elastography,
MICCAI, 2020, in press, pdf
|
 |
86. N. Jafarpisheh*, I. M. Rosado-Mendez, T. J. Hall, and H. Rivaz,
Evaluation of Contrast-to-Noise Ratio of Parametric Images of Regularized Estimates of Quantitative Ultrasound Parameters, IEEE IUS, 2020, in press.
|
 |
85. S. Goudarzi*, A. Asif, and H. Rivaz,
Ultrasound Beamforming using MobileNetV2, IEEE IUS, 2020, in press.
Ranked First (tied) in Challenge on Ultrasound Beamforming with Deep Learning (CUBDL).
|
 |
84. S. Goudarzi*, A. Asif, and H. Rivaz,
Angular Apodization Estimation Using Independent Component Analysis in Coherent Plane- Wave Compounding, IEEE IUS, 2020, in press.
|
 |
83. M. Ashikuzzaman* T. Hall, H. Rivaz,
Adaptive Data Function for Robust Ultrasound Elastography, IEEE IUS, 2020, in press
|
 |
82. P. Chalangari*, T. Fevens, H. Rivaz,
3D Human Knee Flexion Angle Estimation Using Deep Convolutional Neural Networks, IEEE EMBC, 2020, in press.
|
 |
81. M. Aktar*, Y. Xiao, D Tampieri, H. Rivaz, M. Kersten-Oertel, A Radiomics-based Machine Learning Approach to Assess Collateral Circulation in Ischemic Stroke on Non-contrast Computed Tomography, MICCAI CLIP Workshop, 2020, in press.
|
 |
80. A. KZ. Tehrani*, M. Amiri*, I. Rosado-Mendez, T.J. Hall, H. Rivaz,
A Pilot Study on Scatterer Density Classification of Ultrasound Images Using Deep Neural Networks, IEEE EMBC, 2020, in press
|
 |
79. M. Mirzaei*, A. Asif and H. Rivaz,
Synthetic aperture with high lateral sampling frequency for ultrasound elastography, IEEE EMBC, 2020, in press
|
 |
78. A. KZ. Tehrani*, M. Amiri*, H. Rivaz,
Real-time and High Quality Ultrasound Elastography Using Convolutional Neural Network by Incorporating Analytic Signal, IEEE EMBC, 2020, in press
|
 |
77. B. Behboodi*, M. Fortin, C. J.Belasso*, R. Brooks, and H. Rivaz,
Receptive Field Size as a Key Design Parameter for Ultrasound Image Segmentation with U-Net, IEEE EMBC, 2020, in press
|
 |
76. M. Amiri*, A. KZ. Tehrani*, H. Rivaz,
Segmentation of Ultrasound Images based on Scatterer Density using U-Net, IEEE EMBC, 2020, in press.
|
 |
75. A. Zayed*, G. Cloutier and H. Rivaz,
Automatic Frame Selection using CNN in Ultrasound Elastography, IEEE EMBC, 2020, in press.
|
 |
74. M. Ashikuzzaman* and H. Rivaz,
Incorporating Multiple Observations in Global Ultrasound Elastography, IEEE EMBC, 2020, in press
|
 |
73. M. Ashikuzzaman*, H. Rivaz,
Denoising RF Data via Robust Principal Component Analysis: Results in Ultrasound Elastography, IEEE EMBC, 2020, in press
|
 |
72. N. Kheirkhah, S. Dempsey, H. Rivaz, A. Samani, and A. Sadeghi-Naini, A Tissue Mechanics Based Method to Improve Tissue Displacement Estimation in Ultrasound Elastography, IEEE EMBC, 2020, in press.
|
 |
71. N. Jafarpisheh*, I. M. Rosado-Mendez, T. J. Hall, and H. Rivaz,
Regularized Estimation of Effective Scatterer Size and Acoustic Concentration Quantitative Ultrasound Parameters Using Dynamic Programming, IEEE EMBC, 2020, in press.
|
 |
70. S. Goudarzi*, A. Asif, and H. Rivaz,
High Frequency Ultrasound Image Recovery Using Tight Frame Generative Adversarial Networks, IEEE EMBC, 2020, in press.
|
 |
69. B. Behboodi*, M. Amiri*, R. Brooks, H. Rivaz,
Breast lesion segmentation in ultrasound images with limited annotation data,
IEEE ISBI 2020, pp 1834-1837
pdf.
|
2019:
|
|
Journal Papers: |
 |
68. M. Mirzaei*, A. Asif, H. Rivaz,
Combining Total Variation Regularization with Window-based Time Delay Estimation in Ultrasound Elastography,
IEEE Trans. Medical Imaging (TMI), 2019, Vol 38, Issue 12, pp 2744-2754
IEEE Xplore, pdf, supplementary material, code.
|
 |
67. M. Ashikuzzaman*, C.J. Gauthier, H. Rivaz,
Global Ultrasound Elastography in Spatial and Temporal Domains,
IEEE Trans. Ultrasonics Ferroelectrics Frequency Control (TUFFC), 2019, Vol 66, pp 876-887
IEEE Xplore,
pdf, supplementary material, code.
|
 |
66. M. Fortin, A Rizk, S Frenette, M Boily, H. Rivaz,
Ultrasonography of multifidus muscle morphology and function in ice hockey players with and without low back pain,
Physical Therapy in Sport, May 2019, pp 77-85
Elsevier, pdf.
|
 |
65. M.D. Horeh*, A. Asif, H. Rivaz,
Analytical Minimization-Based Regularized Sub-Pixel Shear Wave Tracking for Ultrasound Elastography,
IEEE Trans. Ultrasonics Ferroelectrics Frequency Control (TUFFC), 2019, Vol 66, pp 285 - 296
IEEE Xplore, pdf, supplementary material.
|
 |
64. N. Masoumi*, Y. Xiao*, H. Rivaz,
ARENA: Inter-modality affine registration using evolutionary strategy,
International Journal of Computer Assisted Radiology and Surgery (Springer IJCARS), 2019, Vol 14, pp 441-450
Springer, pdf.
|
 |
63. HS Hashemi*, S Fallone, M Boily, A Towers, RD Kilgour H. Rivaz,
Assessment of Mechanical Properties of Tissue in Breast Cancer-Related Lymphedema Using Ultrasound Elastography,
IEEE Trans. Ultrasonics Ferroelectrics Frequency Control (TUFFC), 2019, vol 66, pp 541-550
IEEE Xplore, pdf, supplementary material.
|
| |
Conf. Papers: |
 |
62. M. Amiri*, R. Brooks, H. Rivaz,
Fine tuning U-Net for ultrasound image segmentation: which layers?,
MICCAI MIL3ID Workshop, 2019, pp 235-242
Springer, pdf
|
 |
61. W Xia, M Fortin, J Ahn, H. Rivaz, M Battie, T Peters, and Y Xiao,
Automatic paraspinal muscle segmentation in patients with lumbar pathology using deep convolutional neural network,
MICCAI 2019, pp 318-325 Springer, pdf
|
 |
60. A. Zayed*, H. Rivaz,
Automatic Frame Selection Using MLP Neural Network in Ultrasound Elastography,
ICIAR, Springer, Cham, 2019, pp 462-472
Springer, pdf
|
 |
59. B. Behboodi*, H. Rivaz,
Ultrasound segmentation using U-Net: learning from simulated data and testing on real data,
IEEE EMBC, 2019, pp 6628-6631
IEEE Xplore
|
 |
58. A. Zayed*, H. Rivaz,
Fast Approximate Time-Delay Estimation in Ultrasound Elastography Using Principal Component Analysis,
IEEE EMBC 2019, pp. 6204-6207
IEEE Xplore,
|
 |
57. Z. Vajihi*, I. Rosado-Mendez, T.J. Hall, H. Rivaz,
L1 and L2 Norm Regularization of Acoustic Attenuation And Backscatter Coefficients Using Dynamic Programming, IEEE ISBI 2019, pp. 1749-1752
IEEE Xplore, pdf
|
 |
56. M. Ashikuzzaman*, C Belasso, C Gauthier, H. Rivaz,
Suppressing Clutter Components in Ultrasound Color Flow Imaging Using Robust Matrix Completion Algorithms: Simulation and Phantom Study, IEEE ISBI 2019, pp. 745-749
|
 |
55. M. Mirzaei*, A. Asif, H. Rivaz,
Ultrasound elastography utilizing pre-beamformed data, IEEE ISBI 2019, pp. 1725-1728
|
|
54. S. Goudarzi*, A. Asif, H. Rivaz,
Multi-focus ultrasound imaging using generative adversarial networks, IEEE ISBI 2019, pp. 1118-1121
IEEE Xplore, pdf
|
2018:
|
|
Journal Papers: |
 |
53. Z. Vajihi*, I. Rosado-Mendez, T.J. Hall, H. Rivaz,
Low Variance Estimation of Backscatter Quantitative Ultrasound Parameters Using Dynamic Programming,
IEEE Trans. Ultrasonics Ferroelectrics Frequency Control (TUFFC), vol 65, Nov 2018, pp 2042-2053
IEEE Xplore, pdf.
|
 |
52. R Shams*, Y Xiao*, F Hebert, M Abramowitz, R Brooks, H. Rivaz,
Assessment of Rigid Registration Quality Measures in Ultrasound-Guided Radiotherapy,
IEEE Trans. Medical Imaging, 2018, vol 37, pp 428-437
IEEE Xplore, pdf.
|
 |
51. M. Ghasemi Amidabadi*, M. Omair Ahmad, H. Rivaz,
Supervised Classification of the Accuracy of the Time Delay Estimation in Ultrasound Elastography,
IEEE Trans. Ultrasonics Ferroelectrics Frequency Control (TUFFC), 2018, vol 65, pp 21-29
IEEE Xplore, pdf.
|
 |
50. P. Khavari*, A. Asif, H. Rivaz,
NonLocal Coherent Denoising Of RF Data For Ultrasound Elastography,
Journal of Healthcare Engineering, (Invited manuscript, APC waived), 2018,
pdf.
|
 |
49. Y Xiao*, M Fortin*, M Battie, H Rivaz,
Population-averaged MRI atlases for automated image processing and assessments of lumbar paraspinal muscles, European Spine Journal, 2018, Vol 27, Issue 10, pp 2442-2448
Springer , pdf.
|
 |
48. Y. Xiao*, M. Boily, H. S. Hashemi, H. Rivaz,
High-Dynamic-Range Ultrasound: Application for Imaging Tendon Pathology,
Ultrasound in Medicine and Biology (UMB), July 2018, Vol 44, Issue 7, Pages 1525-1532
sciencedirect, pdf.
|
 |
47. Y. Xiao*, L. Eikenes, I. Reinertsen, H. Rivaz,
Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection,
International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2018, Vol 13, Issue 3, pp 457-467
Springer, pdf.
|
 |
46. Y Xiao*, H Rivaz, H Kasuya, S Yokosako, C Mindru, J Teitelbaum, D Sirhan, D Sinclair, M Angle, B Lo,
Intra-operative video characterization of carotid artery pulsation patterns in case series with post- endarterectomy hypertension and hyperperfusion syndrome, Translational Stroke Research, 2018, Vol 9, Issue 5, pp 452-458
Springer, pdf.
|
| |
Conf. Papers: |
 |
45. G. Kibria*, H. Rivaz,
GLUENet: Ultrasound Elastography Using Convolutional Neural Network,
MICCAI POCUS 2018, pp 21-28
Springer, pdf, short version on arXiv.
|
 |
44. P. Khavari*, A. Asif, H. Rivaz,
Non-local Super Resolution in Ultrasound Imaging,
IEEE MMSP 2018
In press, pdf.
|
 |
43. H. S. Hashemi*, S. Fallone, M. Boily, A. Towers, R. Kilgour, H. Rivaz,
Ultrasound Elastography of Breast Cancer-Related Lymphedema,
IEEE ISBI 2018, pp 1491-1495
IEEE Xplore, pdf.
|
 |
42. H. Khodadadi*, A. Aghdam, H. Rivaz,
Direct Strain Estimation in Ultrasound Elastography Using A Novel Dynamic Programming Approach,
IEEE ISBI 2018, pp 1182-1186
IEEE Xplore, pdf.
|
2017:
|
|
Journal Papers: |
 |
41. H. Hashemi*, H. Rivaz,
Global Time-Delay Estimation in Ultrasound Elastography,
IEEE Trans. Ultrasonics Ferroelectrics Frequency Control (TUFFC), Oct. 2017, vol 64, pp 1625-1636, (Among Editor's Selection of Articles in TUFFC in 2017, Dec 2018)
IEEE Xplore, pdf, code.
|
 |
40. M. Omidyeganeh*, Y. Xiao*, M. O. Ahmad, H. Rivaz,
Estimation of Strain Elastography from Ultrasound Radio-Frequency Data by Utilizing Analytic Gradient of the Similarity Metric,
IEEE Trans. Medical Imaging, 2017, vol 36, pp 1347-1358
IEEE Xplore, pdf.
|
 |
39. S. R. Mousavi, H. Rivaz, A. Sadeghi-Naini, G. Czarnota, A. Samani,
Breast Ultrasound Elastography using Full Inversion Based Elastic Modulus Reconstruction,
IEEE Trans. Computational Imaging, 2017, vol 3, pp 774-782
IEEE Xplore, pdf.
|
 |
38. Y. Xiao*, M. Fortin*, G. Unsgard, H. Rivaz, I. Reinertsen,
REtroSpective Evaluation of Cerebral Tumors (RESECT): a clinical database of pre-operative MRI and intra-operative ultrasound in low-grade glioma surgeries,
Medical Physics, 2017, vol 44, pp 3875-3882
MedPhys, pdf,
Ultrasound, MRI and landmarks, Direct Link
|
 |
37. S. R. Mousavi, H. Rivaz, G. Czarnota, A. Samani, A. Sadeghi-Naini,
Ultrasound Elastography of Prostate Using an Unconstrained Modulus Reconstruction Technique: A Pilot Clinical Study,
Translational Oncology, 2017, vol 10, pp 744-751
Translational Oncology, pdf.
|
 |
36. M. Fortin*, M. Omidyeganeh*, M. O. Ahmad, M. Crites-Battie, H. Rivaz,
Evaluation of an automated thresholding algorithm for the quantification of paraspinal muscle composition from MRI images, Springer BioMedical Engineering Online, 2017 22;16(1):61.
pdf, Springer, Code and instructions.
|
| |
Conf. Papers: |
 |
35. N. Masoumi*, Y. Xiao*, H. Rivaz,
MARCEL (inter-Modality Affine Registration with CorELation ratio): An Application for Brain Shift Correction in Ultrasound-Guided Brain Tumor Resection,
BrainLes MICCAI workshop, Springer LNCS, 2018, pp 55-63
Springer, pdf.
|
 |
34. Y. Xiao*, A. Alamer V. Fonov, B. Lo, D Tampieri, D.L. Collins, H. Rivaz M. Kersten-Oertl,
Towards automatic collateral circulation score evaluation in ischemic stroke using image decompositions and support vector machines,
Switch 2017 MICCAI workshop , pp 158-167
Springer, pdf.
|
 |
33. Y. Xiao*, D. De Nigris, I. Gerard, Y. Ma, D Tampieri, D.L. Collins, H. Rivaz,
Automatic registration of MRI and transcranial ultrasound for the analysis of neurological disorders,
ISMRM 2017
ISMRM, pdf.
|
 |
32. M.G. Amidabadi*, M.O. Ahmad, H. Rivaz,
Automatic Accuracy Assessment of Ultrasound Elastography Using Correlation Profile and Prior Information of Displacement Continuity,
IEEE GlobalSIP 2017, pp 755-759
IEEE GlobalSIP, pdf.
|
 |
31. M. D. Horeh*, A. Asif, H. Rivaz,
Regularized Tracking of Shear-Wave in Ultrasound Elastography,
The 42nd IEEE Int. Conference on Acoustic, Speech and Signal Processing (ICASSP), New Orleans, LA, 2017, pp 6264-6268
IEEE Xplore, pdf.
|
 |
30. H. Hashemi*, M. Boily, P. Martineau H. Rivaz,
Ultrasound Elastography: Efficient Estimation of Tissue Displacement Using an Affine Transformation Model, SPIE Medical Imaging, Orlando, FL, 2017
Proc. SPIE 10139, pdf.
|
2016:
|
|
 |
29. H. Zhou*, H. Rivaz,
Registration of Pre- and Post-resection Ultrasound Volumes with Non-corresponding Regions in Neurosurgery,
IEEE Journal Biomedical Health Informatics JBHI, 2016, vol 20, pp 1240-1249(selected for submission of full paper to IEEE JBHI, only 10 selections out of 2948 submissions to EMBC)
IEEE Xplore, pdf, supplementary material.
|
 |
28. R. Shams*, M. Boily, P. Martineau, H. Rivaz,
Dynamic Programing on a Tree for Ultrasound Elastography,
SPIE Medical Imaging, San Diego, 2016, vol 9790, (Finalist for a Robert F. Wagner All Conference Best Student Paper Award)
SPIE Digital Lib, pdf.
|
2015:
|
|
Journal Papers: |
 |
27. H. Rivaz, Chen, S, Collins, DL.,
Automatic Deformable MR-Ultrasound Registration for Image-Guided Neurosurgery,
IEEE Trans. Medical Imaging, 2015, vol 34, pp 366-380
(IEEE Xplore), pdf, Data ReadMe text file,
Ultrasound, MRI and manually selected landmarks (591MB zip file).
|
 |
26. H. Rivaz, Collins, DL.,
Deformable Registration of Pre-Operative MR, Pre-Resection Ultrasound and Post-Resection Ultrasound Images of Neurosurgery,
International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2015, vol 10, pp 1017-1028
Springer, pdf.
|
 |
25. H. Rivaz, Collins, DL.,
Near Real-Time Robust Nonrigid Registration of Volumetric Ultrasound Images For Neurosurgery,
Ultrasound in Medicine and Biology, 2015, vol 41, pp 574-587
ScienceDirect, pdf.
|
 |
24. Karimaghaloo, Z, H. Rivaz, Arnold, D, Collins, DL. Arbel, T,
Temporal Hierarchical Adaptive Texture CRF for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI,
IEEE Trans. Medical Imaging, 2015, vol 34, pp 1227-1241
IEEE Xplore, pdf.
|
| |
Conf. Papers: |
 |
23. H. Zhou*, H. Rivaz,
Robust Deformable Registration of Pre- and Post-resection Ultrasound Volumes for Visualization of Residual Tumor in Neurosurgery,
IEEE EMBC, 2015, pp 141 - 144, (selected for submission of full paper to IEEE JBHI, only 10 selections out of 2948 submissions to EMBC)
IEEE Xplore, pdf.
|
 |
22. H. Khodadadi*, A. Aghdam, H. Rivaz,
Edge-Preserving Ultrasonic Strain Imaging with Uniform Precision,
IEEE EMBC, 2015, pp 3835 - 3838
IEEE Xplore, pdf.
|
2014:
|
|
Journal Papers: |
 |
21. H. Rivaz, Karimaghaloo, Z, Fonov, V, Collins, DL.,
Nonrigid Registration of Ultrasound and MRI Using Contextual Conditioned Mutual Information,
IEEE Trans. Medical Imaging, 2014, vol. 33 pp 708-725
(IEEE Xplore), pdf.
|
 |
20. H. Rivaz, Karimaghaloo, Z, Collins, DL.,
Self-Similarity Weighted Mutual Information: a New Non-rigid Image Registration Metric,
Medical Image Analysis, 2014, vol. 18 pp 343-358
(ScienceDirect), pdf.
|
 |
19. H. Rivaz, Boctor, E., Choti, M., Hager,
G., Ultrasound Elastography Using Multiple Images, Medical Image Analysis, February 2014, vol. 18 pp 314-329
(ScienceDirect), pdf.
|
| |
Conference Papers: |
 |
18. H. Rivaz, Collins, DL.,
Simulation of Ultrasound Images for Validation of MR to Ultrasound Registration in Neurosurgery,
AECAI MICCAI, 2014 pp 23-32
(Springer LNCS), pdf.
|
Before 2014:
|
|
 |
17. Karimaghaloo, Z., H. Rivaz, Arnold, D., Collins, DL, Arbel, T,
Adaptive Voxel, Texture and Temporal CRF for Detection of MS Lesions in Brain MRI,
MICCAI, Nagoya, Japan, Sept. 2013 pp 543-550 [Acceptance rate: 32%] pdf.
|
 |
16. H. Rivaz, Collins, D.L., Self-Similarity Weighted Mutual Information:
a New Non-rigid Image Registration Metric, Medical Image Computing and Computer Assisted
Intervention, MICCAI, Oct 2012, pp 91-98 [Acceptance rate: 30%]. pdf.
|
 |
15. H. Rivaz, Boctor, E., Choti, M., Hager, G., Real-Time Regularized Ultrasound
Elastography, IEEE Trans. Medical Imaging, April 2011, vol. 30 pp 928-945
pdf Code.
|
 |
14. H. Rivaz, Boctor, E., Foroughi, P., Zellars, R., Fichtinger, G.,
Hager, G., Ultrasound Elastography: a Dynamic Programming Approach, IEEE
Trans. Medical Imaging, Oct. 2008, vol. 27 pp 1373-1377 pdf Code.
|
 |
13. H. Rivaz, Boctor, E., Choti, M., Hager, G., Ultrasound Elastography Using Three Images,
Medical Image Computing and Computer Assisted Intervention, MICCAI, Toronto, Canada,
Sept. 2011, pp 371-378 [Acceptance rate: 30%] pdf Code.
|
 |
12. Foroughi, P., H. Rivaz, Fleming, I., Hager, G., Boctor, E.
Tracked Ultrasound Elastography (TrUE), Medical Image Computing and Computer Assisted Intervention,
MICCAI, Beijing, China, Sept. 2010, pp 9-16 [Acceptance rate: 32%] pdf.
|
 |
11. H. Rivaz, Kang, H., Stolka, P., G. Hager, Boctor, E.
Novel reconstruction and feature exploitation techniques for sensorless freehand 3D ultrasound,
SPIE Medical Imaging, 2010, pp 762911-762919 pdf.
|
 |
10. H. Rivaz, Kapoor, A., Fleming, I., Hager, G., Boctor, E.
A novel method for monitoring liver ablation using ultrasound elastography,
SPIE Medical Imaging, 2010, 7629131-7629138 pdf.
|
 |
9. H. Rivaz, Foroughi, P., Fleming, I., Zellars, R., Boctor, E., Hager,
G., Tracked Regularized Ultrasound Elastography for Targeting Breast
Radiotherapy, Medical Image Computing and Computer Assisted Intervention,
MICCAI, London, UK, Sept. 2009, pp 507-515 [Acceptance rate: 33%] pdf.
|
 |
8. H. Rivaz, Shinagawa, Y., Liang, J., Physical Priors in Virtual Colonoscopy, SPIE Medical Imaging 2009, pp 7260191-72601912 pdf.
|
 |
7. H. Rivaz, Fleming, I., Assumpcao, L., Fichtinger, G., Hamper, U.,
Choti, M., Hager, G., Boctor, E., Ablation Monitoring with Elastography: 2D
In-vivo and 3D Ex-vivo Studies, Medical Image Computing and Computer Assisted
Intervention, MICCAI, New York, NY, Sept. 2008, pp 458-466 [Acceptance rate: 30%]
pdf.
|
 |
6. H. Rivaz, Fleming, L., Matinfar, M, Ahmad, O, Kamen, A, Choti, M, Hager, G., Boctor, E. Ablation Monitoring
with a Regularized 3D Elastography Technique, IEEE Int. Ultrasonics Symposium,
Beijing, China, Oct. 2008, pp 308-312 pdf.
|
 |
5. H. Rivaz, Rohling, R., An Active Dynamic Vibration Absorber for a Hand-Held Vibro-Elastography Probe, ASME Journal of Vibration Acoustics
pdf.
|
 |
4. H. Rivaz, Zellars, R., Hager, G. Fichtinger, G., Boctor, E., Beam
Steering Approach to Speckle Characterization and Out-of-Plane Motion Estimation
in Real Tissue, IEEE Int. Ultrasonics Symposium, New York, NY, Oct. 2007 pp
781-784 pdf.
|
 |
3. H. Rivaz, Boctor, E., Fichtinger, G., A Robust Meshing and
Calibration Approach for Sensorless Freehand 3D Ultrasound, SPIE Medical
Imaging, San Diego, CA, Feb. 2007, Vol. 6513, pp 181-188 pdf.
|
 |
2. H. Rivaz, Rohling, R., A Hand-Held Probe for Vibro-Elastography, Medical Image Computing and Computer Assisted
Intervention, MICCAI, 2006, pp 613-620 pdf.
|
 |
1. H. Rivaz, Boctor, E., Fichtinger, G., Ultrasound Speckle Detection
using Low Order Statistics, IEEE Int. Ultrasonics Symposium, Vancouver, Canada,
Oct. 2006, pp 2092-2095 pdf.
|
Patents
|
 |
P3. H. Rivaz, Boctor, E., Hager, G. and Fichtinger, G., Robust and Accurate
Freehand 3D ultrasound, US patent 8,559,685 (Awarded)
pdf
|
 |
P2. H. Rivaz, Hager, G. Boctor, E., and Fleming, I. Method and System
for Processing Ultrasound Data, US patent US 8,824,762 (Awarded)
pdf
|
 |
P1. Boctor, E., Fichtinger, G., Hager, G. and H. Rivaz, Apparatus and
Method for Computing 3D Ultrasound Elasticity Images, US 0306384 (Pending)
pdf
|
Rejections
|
| |
Congrats if you made it this far on my page. Now to see some of my rejections, click here!
|
Teaching
|
|
COEN 243, C++ Programming Methodology I (Fall 2014)
ENGR 371, Probability & Statistics (Winter 2015)
ENCS 6161 (in pdf), Stochastic Process (Fall 2015)
ELEC 498/691 , Medical Image Processing (Winter 2016)
ELEC 498/691 , Medical Image Processing (Fall 2016)
ENGR 371, Probability & Statistics (Summer 2017)
ELEC 444/6661, Medical Image Processing (Fall 2017)
ENGR 371, Probability & Statistics (Winter 2018)
ELEC 444/6661, Medical Image Processing (Fall 2018)
ENGR 371, Probability & Statistics (Winter 2019)
ELEC 444/6661, Medical Image Processing (Fall 2019)
ENGR 371, Probability & Statistics (Winter 2020)
|
