@article {Janssen2020a, title = {Navigated tissue characterization during skin cancer surgery}, journal = {Int J Comput Assist Radiol Surg}, year = {In Press}, month = {05/2020}, abstract = {

Purpose:\ Basal cell carcinoma (BCC) is the most commonly diagnosed skin cancer and is treated by surgical resection. Incomplete tumor removal requires surgical revision, leading to significant healthcare costs and impaired cosmesis. We investigated the clinical feasibility of a surgical navigation system for BCC surgery, based on molecular tissue characterization using rapid evaporative ionization mass spectrometry (REIMS).

Methods:\ REIMS enables direct tissue characterization by analysis of cell-specific molecules present within surgical smoke, produced during electrocautery tissue resection. A tissue characterization model was built by acquiring REIMS spectra of BCC, healthy skin and fat from ex vivo skin cancer specimens. This model was used for tissue characterization during navigated skin cancer surgery. Navigation was enabled by optical tracking and real-time visualization of the cautery relative to a contoured resection volume. The surgical smoke was aspirated into a mass spectrometer and directly analyzed with REIMS. Classified BCC was annotated at the real-time position of the cautery. Feasibility of the navigation system, and tissue classification accuracy for ex vivo and intraoperative surgery were evaluated.

Results:\ Fifty-four fresh excision specimens were used to build the ex vivo model of BCC, normal skin and fat, with 92\% accuracy. While 3 surgeries were successfully navigated without breach of sterility, the intraoperative performance of the ex vivo model was low (\< 50\%). Hypotheses are: (1) the model was trained on heterogeneous mass spectra that did not originate from a single tissue type, (2) during surgery mixed tissue types were resected and thus presented to the model, and (3) the mass spectra were not validated by pathology.

Conclusion:\ REIMS-navigated skin cancer surgery has the potential to detect and localize remaining tumor intraoperatively. Future work will be focused on improving our model by using a precise pencil cautery tip for burning localized tissue types, and having pathology-validated mass spectra.

}, keywords = {Intraoperative surgical resection margin assessment, Model-guided surgery, Optical navigation, Real-time tissue characterization}, doi = {10.1007/s11548-020-02200-4}, url = {https://doi.org/10.1007/s11548-020-02200-4}, author = {Natasja Janssen and Martin Kaufmann and Alice Santilli and Amoon Jamzad and Vanderbeck Kaitlin and Kevin Ren and Tamas Ungi and Parvin Mousavi and John Rudan and Doug McKay and Amy Wang and Gabor Fichtinger} } @article {Hu2022, title = {Real-time automatic tumor segmentation for ultrasound-guided breast-conserving surgery navigation}, journal = {International Journal of Computer Assisted Radiology and Surgery}, year = {In Press}, month = {05/2022}, doi = {10.1007/s11548-022-02658-4}, url = {https://doi.org/10.1007/s11548-022-02658-4}, author = {Zoe Hu and Paola V. Nasute Fauerbach and Chris Yeung and Tamas Ungi and John Rudan and C. Jay Engel and Parvin Mousavi and Gabor Fichtinger and Doris Jabs} } @article {Kitner2022a, title = {Automated Automatic catheter modelling in 3D transrectal ultrasound images from high-dose-rate prostate brachytherapy using a deep learning and feature extraction pipeline}, year = {2022}, month = {06/2022}, publisher = {Canadian Organization of Medical Physicists}, author = {Nicole Kitner and Jessica R. Rodgers and Tamas Ungi and Martin Korzeniowski and Timothy Olding and C.P. Joshi and Parvin Mousavi and Gabor Fichtinger} } @article {Kitner2022a, title = {Automated catheter localization in ultrasound images from High-dose-rate prostate brachytherapy using deep learning and feature extraction}, year = {2022}, month = {09/2022}, publisher = {Canadian Association for Radiation Oncologists}, author = {Nicole Kitner and Jessica R. Rodgers and Tamas Ungi and Timothy Olding and C.P. Joshi and Parvin Mousavi and Gabor Fichtinger and Martin Korzeniowski} } @article {Kitner2022a, title = {Automated Catheter Segmentation in 3D Ultrasound Images from High-Dose-Rate Prostate Brachytherapy}, year = {2022}, month = {02/2022}, publisher = {Imaging Network of Ontario}, address = {Online}, author = {Nicole Kitner and Jessica R. Rodgers and Tamas Ungi and Martin Korzeniowski and Timothy Olding and C.P. Joshi and Parvin Mousavi and Gabor Fichtinger} } @article {Connolly2022c, title = {Bridging 3D Slicer and ROS2 for Image-Guided Robotic Interventions}, journal = {Sensors}, volume = {22}, year = {2022}, month = {07/2022}, doi = {https://doi.org/10.3390/s22145336}, author = {Laura Connolly and Anton Degeut and Simon Leonard and Junichi Tokuda and Tamas Ungi and Axel Krieger and Peter Kazanzides and Parvin Mousavi and Gabor Fichtinger and Russell H. Taylor} } @conference {Connolly2022, title = {Feasibility of combined optical and acoustic imaging for surgical cavity scanning}, booktitle = {SPIE Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling}, volume = {12034}, year = {2022}, month = {04/2022}, address = {San Diego (online)}, abstract = { PURPOSE: Over 30\% of breast conserving surgery patients must undergo repeat surgery to address incomplete tumor resection. We hypothesize that the addition of a robotic cavity scanning system can improve the success rates of these procedures by performing additional, intraoperative imaging to detect left-over cancer cells. In this study, we assess the feasibility of a combined optical and acoustic imaging approach for this cavity scanning system. METHODS: Dual-layer tissue phantoms are imaged with both throughput broadband spectroscopy and an endocavity ultrasound probe. The absorbance and transmittance of the incident light from the broadband source is used to characterize each tissue sample optically. Additionally, a temporally enhanced ultrasound approach is used to distinguish the heterogeneity of the tissue sample by classifying individual pixels in the ultrasound image with a support vector machine. The goal of this combined approach is to use optical characterization to classify the tissue surface, and acoustic characterization to classify the sample heterogeneity. RESULTS: Both optical and acoustic characterization demonstrated promising preliminary results. The class of each tissue sample is distinctly separable based on the transmittance and absorption of the broadband light. Additionally, an SVM trained on the temporally enhance ultrasound signals for each tissue type, showed 82\% linear separability of labelled temporally enhanced ultrasound sequences in our test set. CONCLUSIONS: By combining broadband and ultrasound imaging, we demonstrate a potential non-destructive imaging approach for this robotic cavity scanning system. With this approach, our system can detect both surface level tissue characteristics and depth information. Applying this to breast conserving surgery can help inform the surgeon about the tissue composition of the resection cavity after initial tumor resection.}, doi = {https://doi.org/10.1117/12.2611964}, author = {Laura Connolly and Amoon Jamzad and Arash Nikniazi and Rana Poushimin and Jean Michel Nunzi and John Rudan and Gabor Fichtinger and Parvin Mousavi} } @conference {connolly2022b, title = {An open-source testbed for developing image-guided robotic tumor-bed inspection}, booktitle = {Imaging Network of Ontario (ImNO) Symposium}, year = {2022}, author = {Laura Connolly and Amoon Jamzad and Arash Nikniazi and Rana Poushimin and Andras Lasso and Kyle R. Sunderland and Tamas Ungi and Jean Michel Nunzi and John Rudan and Gabor Fichtinger and Parvin Mousavi} } @article {Fooladgar2022, title = {Uncertainty estimation for margin detection in cancer surgery using mass spectrometry}, journal = {International Journal of Computer Assisted Radiology and Surgery}, year = {2022}, month = {09/2022}, type = {Journal}, doi = {https://doi.org/10.1007/s11548-022-02764-3}, author = {Fahimeh Fooladgar and Amoon Jamzad and Laura Connolly and Alice Santilli and Martin Kaufmann and Kevin Ren and Purang Abolmaesumi and John Rudan and Doug McKay and Gabor Fichtinger and Parvin Mousavi} } @article {Connolly2021c, title = {Combined Mass Spectrometry and Histopathology Imaging for Perioperative Tissue Assessment in Cancer Surgery}, journal = {Journal of Imaging}, volume = {7}, number = {203}, year = {2021}, month = {10/2021}, type = {Article}, abstract = {

Mass spectrometry is an effective imaging tool for evaluating biological tissue to detect cancer. With the assistance of deep learning, this technology can be used as a perioperative tissue assessment tool that will facilitate informed surgical decisions. To achieve such a system requires the development of a database of mass spectrometry signals and their corresponding pathology labels. Assigning correct labels, in turn, necessitates precise spatial registration of histopathology and mass spectrometry data. This is a challenging task due to the domain differences and noisy nature of images. In this study, we create a registration framework for mass spectrometry and pathology images as a contribution to the development of perioperative tissue assessment. In doing so, we explore two opportunities in deep learning for medical image registration, namely, unsupervised, multi-modal deformable image registration and evaluation of the registration. We test this system on prostate needle biopsy cores that were imaged with desorption electrospray ionization mass spectrometry (DESI) and show that we can successfully register DESI and histology images to achieve accurate alignment and, consequently, labelling for future training. This automation is expected to improve the efficiency and development of a deep learning architecture that will benefit the use of mass spectrometry imaging for cancer diagnosis.

}, doi = {https://doi.org/10.3390/jimaging7100203}, author = {Laura Connolly and Amoon Jamzad and Martin Kaufmann and Catriona E. Farquharson and Kevin Ren and John Rudan and Gabor Fichtinger and Parvin Mousavi} } @article {Fichtinger2021, title = {Design of an Ultrasound-Navigated Prostate Cancer Biopsy System for Nationwide Implementation in Senegal}, journal = {Journal of Imaging}, volume = {7}, number = {8}, year = {2021}, month = {08/2021}, pages = {154}, abstract = {

This paper presents the design of NaviPBx, an ultrasound-navigated prostate cancer biopsy system. NaviPBx is designed to support an affordable and sustainable national healthcare program in Senegal. It uses spatiotemporal navigation and multiparametric transrectal ultrasound to guide biopsies. NaviPBx integrates concepts and methods that have been independently validated previously in clinical feasibility studies and deploys them together in a practical prostate cancer biopsy system. NaviPBx is based entirely on free open-source software and will be shared as a free open-source program with no restriction on its use. NaviPBx is set to be deployed and sustained nationwide through the Senegalese Military Health Service. This paper reports on the results of the design process of NaviPBx. Our approach concentrates on {\textquotedblleft}frugal technology{\textquotedblright}, intended to be affordable for low{\textendash}middle income (LMIC) countries. Our project promises the wide-scale application of prostate biopsy and will foster time-efficient development and programmatic implementation of ultrasound-guided diagnostic and therapeutic interventions in Senegal and beyond.

}, issn = {2313-433X}, doi = {10.3390/jimaging7080154}, url = {https://www.mdpi.com/2313-433X/7/8/154}, author = {Gabor Fichtinger and Parvin Mousavi and Tamas Ungi and Fenster, Aaron and Purang Abolmaesumi and Gernot Kronreif and Ruiz-Alzola, Juan and Ndoye, Alain and Diao, Babacar and Ron Kikinis} } @conference {CWu2021a, title = {Development of an open-source system for prostate biopsy training in Senegal}, booktitle = {SPIE Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling}, volume = {11598}, year = {2021}, month = {02/2021}, author = {Wu, Catherine O. and Diao, Babacar and Tamas Ungi and Alireza Sedghi and Ron Kikinis and Parvin Mousavi and Gabor Fichtinger} } @conference {Connolly2021, title = {An open-source platform for cooperative semi-autonomous robotic surgery}, booktitle = {IEEE International Conference on Autonomous Systems}, year = {2021}, month = {10/2021}, publisher = {IEEE}, organization = {IEEE}, address = {Montreal, Quebec}, doi = {https://doi.org/10.1109/ICAS49788.2021.9551149}, author = {Laura Connolly and Anton Degeut and Kyle R. Sunderland and Andras Lasso and Tamas Ungi and John Rudan and Russell H. Taylor and Parvin Mousavi and Gabor Fichtinger} } @article {Connolly2021b, title = {A platform for robot-assisted Intraoperative imaging in breast conserving surgery}, year = {2021}, month = {2021}, publisher = {Imaging Network of Ontario Symposium}, address = {Online}, author = {Laura Connolly and Kyle R. Sunderland and Andras Lasso and Anton Degeut and Tamas Ungi and John Rudan and Russell H. Taylor and Parvin Mousavi and Gabor Fichtinger} } @conference {Connolly2020a, title = {Classification of tumor signatures from electrosurgical vapors using mass spectrometry and machine learning: a feasibility study}, booktitle = {Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions and Modeling}, volume = {11315}, year = {2020}, month = {2020}, publisher = {SPIE}, organization = {SPIE}, address = {Houston, Texas, United States}, doi = {https://doi.org/10.1117/12.2549343}, author = {Laura Connolly and Amoon Jamzad and Martin Kaufmann and Rachel Rubino and Alireza Sedghi and Tamas Ungi and Mark Asselin and Scott Yam and John Rudan and Christopher Nicol and Gabor Fichtinger and Parvin Mousavi} } @conference {Connolly2019a, title = {Mechanically-Controlled Spectroscopic Imaging for Tissue Classification}, booktitle = {SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling}, volume = {10951}, year = {2019}, month = {03/2019}, address = {San Diego, California}, doi = {https://doi.org/10.1117/12.2512481}, author = {Laura Connolly and Tamas Ungi and Andras Lasso and Thomas Vaughan and Mark Asselin and Parvin Mousavi and Scott Yam and Gabor Fichtinger} } @conference {Baum2019a, title = {Step-wise identification of ultrasound-visible anatomical landmarks for 3D visualization of scoliotic spine}, booktitle = {SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling}, volume = {10951}, year = {2019}, month = {03/2019}, address = {San Diego, California}, author = {Zachary M C Baum and Ben Church and Andras Lasso and Tamas Ungi and Christopher Schlenger and Daniel P. Borschneck and Parvin Mousavi and Gabor Fichtinger} } @article {Church2017b, title = {Scoliosis visualization using transverse process landmarks}, year = {2017}, keywords = {scoliosis, Spine, Ultrasound, visualization}, author = {Ben Church}, editor = {Andras Lasso and Christopher Schlenger and Daniel P. Borschneck and Parvin Mousavi and Gabor Fichtinger and Tamas Ungi} } @conference {Church2017, title = {Visualization of scoliotic spine using ultrasound-accessible skeletal landmarks}, booktitle = {SPIE Medical Imaging 2017}, year = {2017}, keywords = {scoliosis, Spine, Ultrasound, visualization}, author = {Ben Church and Andras Lasso and Christopher Schlenger and Daniel P. Borschneck and Parvin Mousavi and Gabor Fichtinger and Tamas Ungi} } @article {Keri2015a, title = {Computerized training system for ultrasound-guided lumbar puncture on abnormal spine models: a randomized controlled trial}, journal = {Canadian Journal of Anesthesia}, volume = {62}, year = {2015}, month = {07/2015}, pages = {777-784}, url = {http://www.ncbi.nlm.nih.gov/pubmed/25804431}, author = {Keri, Zsuzsanna and Devin Sydor and Tamas Ungi and M. Holden and McGraw, Robert C and Parvin Mousavi and Daniel P. Borschneck and Gabor Fichtinger and Melanie Jaeger} } @article {Ungi2014a, title = {Spinal curvature measurement by tracked ultrasound snapshots}, journal = {Ultrasound in Medicine and Biology}, volume = {40}, year = {2014}, month = {02/2014}, pages = {447-54}, author = {Tamas Ungi and Franklin King and Michael Kempston and Keri, Zsuzsanna and Andras Lasso and Parvin Mousavi and John Rudan and Daniel P. Borschneck and Gabor Fichtinger} } @article {Imani2013, title = {Ultrasound-guided Characterization of Interstitial Ablated Tissue Using RF Time Series: Feasibility Study.}, journal = {IEEE transactions on bio-medical engineering}, year = {2013}, month = {01/2013}, abstract = {

This paper presents the results of a feasibility study to demonstrate the application of ultrasound RF time series imaging to accurately differentiate ablated and non-ablated tissue. Methods: For 12 ex vivo and two in situ tissue samples, RF ultrasound signals are acquired prior to, and following, high intensity ultrasound ablation. Spatial and temporal features of these signals are used to characterize ablated and non-ablated tissue in a supervised-learning framework. Results: In crossvalidation evaluation, a subset of four features extracted from RF time series produce a classification accuracy of 84.5\%, and an area under ROC curve of 0.91 for ex vivo data, and an accuracy of 85\% for in situ data. Conclusion: Ultrasound RF time series is a promising approach for characterizing ablated tissue.

}, url = {http://www.ncbi.nlm.nih.gov/pubmed/23335657}, author = {F Imani and Purang Abolmaesumi and Wu, M. and Andras Lasso and E. Clif Burdette and Ghoshal, G and Tamas Heffter and Williams, E and Neubauer, P and Gabor Fichtinger and Parvin Mousavi} } @article {Ungi2012b, title = {Spinal Needle Navigation by Tracked Ultrasound Snapshots}, journal = {IEEE Trans Biomed Eng}, volume = {59}, year = {2012}, month = {10/2012}, pages = {2766-2772}, author = {Tamas Ungi and Purang Abolmaesumi and Rayhan Jalal and Mattea Welch and Irene Ayukawa and Simrin Nagpal and Andras Lasso and Melanie Jaeger and Daniel P. Borschneck and Gabor Fichtinger and Parvin Mousavi} } @article {Imani2012, title = {Ultrasound-guided Characterization of ablated Tissue Using RF Time Series}, year = {2012}, month = {06/2012}, address = {Rosslyn, VA, USA}, author = {F Imani and Mohammad Daoud and Andras Lasso and E. Clif Burdette and Gabor Fichtinger and Purang Abolmaesumi and Parvin Mousavi} } @article {Ungi2012a, title = {Ultrasound-guided spinal needle placement on open source platform}, year = {2012}, month = {02/2012}, address = {Toronto, ON, Canada}, author = {Tamas Ungi and Andras Lasso and Mattea Welch and Rayhan Jalal and Simrin Nagpal and Melanie Jaeger and Daniel P. Borschneck and Parvin Mousavi and Gabor Fichtinger} } @conference {Khallaghi2011, title = {GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images}, booktitle = {SPIE Medical Imaging}, volume = {7964}, number = {1}, year = {2011}, month = {03/2011}, pages = {79642W}, publisher = {SPIE}, organization = {SPIE}, address = {Lake Buena Vista, Florida, USA}, doi = {10.1117/12.878377}, url = {http://link.aip.org/link/?PSI/7964/79642W/1}, author = {Siavash Khallaghi and Purang Abolmaesumi and Ren Hui Gong and Elvis C. S. Chen and Sean Gill and Jonathan Boisvert and David R Pichora and Daniel P. Borschneck and Gabor Fichtinger and Parvin Mousavi} } @conference {Imani2011, title = {Monitoring of Tissue Ablation Using Time Series of Ultrasound RF data}, booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011)}, year = {2011}, month = {09/2011}, pages = {379-386}, address = {Toronto, ON, Canada}, author = {F Imani and Wu, M. and Andras Lasso and E. Clif Burdette and Mohammad Daoud and Gabor Fichtinger and Purang Abolmaesumi and Parvin Mousavi} } @conference {Ghanavati2011, title = {Phantom validation for ultrasound to statistical shape model registration of human pelvis}, booktitle = {SPIE Medical Imaging}, volume = {7964}, number = {1}, year = {2011}, month = {03/2011}, pages = {79642U}, publisher = {SPIE}, organization = {SPIE}, address = {Lake Buena Vista, Florida, USA}, doi = {10.1117/12.876998}, url = {http://link.aip.org/link/?PSI/7964/79642U/1}, author = {Sugantha Ganapathy and Parvin Mousavi and Gabor Fichtinger and Purang Abolmaesumi} } @conference {Ghanavati2010, title = {Multi-Slice to Volume Registration of Ultrasound Data to a Statistical Atlas of Human Pelvis}, booktitle = {SPIE Medical Imaging}, series = {Visualization, Image-Guided Procedures, and Modeling}, volume = {7625}, year = {2010}, month = {23 February 2010}, pages = {76250O-1 {\textendash} 76250O-10}, publisher = {SPIE Digital Library}, organization = {SPIE Digital Library}, address = {San Diego, California, USA}, abstract = {

Identifying the proper orientation of the pelvis is a critical step in accurate placement of the femur prosthesis in the acetabulum in Total Hip Replacement (THR) surgeries. The general approach to localize the orientation of the pelvis coordinate system is to use X-ray fluoroscopy to guide the procedure. An alternative can be employing intra-operative ultrasound (US) imaging with pre-operative CT scan or fluoroscopy imaging. In this paper, we propose to replace the need of pre-operative imaging by using a statistical shape model of the pelvis, constructed from several CT images. We then propose an automatic deformable intensity-based registration of the anatomical atlas to a sparse set of 2D ultrasound images of the pelvis in order to localize its anatomical coordinate system. In this registration technique, we first extract a set of 2D slices from a single instance of the pelvic atlas. Each individual 2D slice is generated based on the location of a corresponding 2D ultrasound image. Next, we create simulated ultrasound images out of the 2D atlas slices and calculate a similarity metric between the simulated images and the actual ultrasound images. The similarity metric guides an optimizer to generate an instance of the atlas that best matches the ultrasound data. We demonstrated the feasibility of our proposed approach on two male human cadaver data. The registration was able to localize a patient-specific pelvic coordinate system with origin translation error of 2 mm and 3.45 mm, and average axes rotation error of 3.5 degrees and 3.9 degrees for the two cadavers, respectively.

}, keywords = {Deformable registration, Freehand ultrasound, Intensity-based registration, Pelvis., Statistical anatomical atlas, Total Hip Replacement}, doi = {10.1117/12.844080}, url = {http://spiedl.aip.org/getabs/servlet/GetabsServlet?prog=normal\&id=PSISDG00762500000176250O000001\&idtype=cvips\&gifs=yes}, author = {Sugantha Ganapathy and Parvin Mousavi and Gabor Fichtinger and Pezhman Foroughi and Purang Abolmaesumi} } @conference {Khallaghi2010, title = {Registration of a Statistical Shape Model of the Lumbar Spine to 3D Ultrasound Images}, booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2010}, year = {2010}, pages = {68-75}, publisher = {Springer}, organization = {Springer}, address = {Beijing, China}, author = {Siavash Khallaghi and Parvin Mousavi and Ren Hui Gong and Sean Gill and Jonathan Boisvert and Gabor Fichtinger and David R Pichora and Daniel P. Borschneck and Purang Abolmaesumi} } @conference {Gill2009a, title = {Biomechanically Constrained Groupwise US to CT Registration of the Lumbar Spine}, booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)}, volume = {5761}, year = {2009}, pages = {803-810}, publisher = {Springer}, organization = {Springer}, address = {London, UK}, isbn = {978-3-642-04267-6}, author = {Sean Gill and Parvin Mousavi and Gabor Fichtinger and Purang Abolmaesumi} } @conference {Lang2009, title = {Fusion of electromagnetic tracking with speckle-tracked 3D freehand ultrasound using an unscented Kalman filter}, booktitle = {SPIE Medical Imaging 2009: Ultrasonic Imaging and Signal Processing}, year = {2009}, author = {Andrew Lang and Parvin Mousavi and Gabor Fichtinger and Purang Abolmaesumi} } @conference {Gill2009, title = {Group-wise Registration of Ultrasound to CT Images of Human Vertebrae}, booktitle = {SPIE Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling}, volume = {7261}, year = {2009}, pages = {na}, author = {Sean Gill and Parvin Mousavi and Gabor Fichtinger and David R Pichora and Purang Abolmaesumi} } @conference {Aboofazeli2009b, title = {A new scheme for curved needle segmentation in three-dimensional ultrasound images}, booktitle = {Proc. IEEE International Symposium on Biomedical Imaging: From Nano to Macro ISBI {\textquoteright}09}, year = {2009}, pages = {1067{\textendash}1070}, doi = {10.1109/ISBI.2009.5193240}, author = {Mohammad Aboofazeli and Purang Abolmaesumi and Parvin Mousavi and Gabor Fichtinger} } @conference {Aboofazeli2009, title = {Tissue characterization using multiscale products of wavelet transform of ultrasound radio frequency echoes}, booktitle = {Proc. Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC 2009}, year = {2009}, pages = {479{\textendash}482}, doi = {10.1109/IEMBS.2009.5335160}, author = {Mohammad Aboofazeli and Purang Abolmaesumi and Gabor Fichtinger and Parvin Mousavi} } @conference {Gill2008, title = {Group-wise Ultrasound to CT Registration of the Lumbar Spine}, booktitle = {7th Symposium of the Imaging Network of Ontario, Toronto}, year = {2008}, pages = {73}, author = {Sean Gill and Parvin Mousavi and Gabor Fichtinger and David R Pichora and Purang Abolmaesumi} } @conference {Gill2008a, title = {Intraoperative Prostate Tracking with Slice-to-Volume Registration in MRI}, booktitle = {20th International Conference of the Society for Medical Innovation and Technology}, year = {2008}, month = {08/2008}, pages = {154-158}, publisher = {Society for Medical Innovation and Technology SMIT}, organization = {Society for Medical Innovation and Technology SMIT}, address = {Vienna, Austria, August 28-31, 2008}, isbn = {3-902087-25-0}, author = {Sean Gill and Purang Abolmaesumi and Siddharth Vikal and Parvin Mousavi and Gabor Fichtinger} } @conference {Gobbi2008, title = {Simulink libraries for visual programming of VTK and ITK}, booktitle = {Workshop on Systems and Architectures for Computer Assisted Interventions, held in conjunction with the 11th International Conference on Medical Image Computing and Computer Assisted Intervention}, year = {2008}, author = {David Gobbi and Parvin Mousavi and K Li and Jing Xiang and Adam Campigotto and Gabor Fichtinger and Purang Abolmaesumi} } @conference {Ahmidi2008, title = {A System for Performance Analysis of Surgeon Dexterity in Percutaneous Needle-based Interventions}, booktitle = {7th Imaging Symposium of the Imaging Network of Ontario}, year = {2008}, author = {Narges Ahmidi and Paweena U-Thainual and Siddharth Vikal and Parvin Mousavi and Iulian Iordachita and Gabor Fichtinger} }