{"id":2447,"date":"2024-05-03T19:24:47","date_gmt":"2024-05-03T19:24:47","guid":{"rendered":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/hossein-sadjadi\/"},"modified":"2024-05-03T19:24:47","modified_gmt":"2024-05-03T19:24:47","slug":"hossein-sadjadi","status":"publish","type":"qsc_member","link":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/hossein-sadjadi\/","title":{"rendered":"Hossein Sadjadi"},"content":{"rendered":"
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Hossein Sadjadi<\/h1>\n<\/div>\n
Postdoctoral Fellow<\/div>\n
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Queen’s University<\/div>\n
Member from 2010<\/em> to 2016<\/em><\/div>\n
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\n\tHossein Sadjadi received his Ph.D. degree in electrical engineering from Queen’s University, Canada, the M.Sc. degree in mechatronics, and the B.Sc. degree in electrical engineering in 2014, 2009 and 2004 respectively. He served as an automation engineer and contributed to the design, planning, and execution of several industrial Siemens SCADA\/DCS projects. He also held a senior mechatronics specialist position and developed various robotic platforms and embedded systems. At Queen’s university, he carried out extensive research pertaining to surgical navigation for robotic image-guided interventional systems. Following graduatuion, he was a postdoctoral researcher with the Laboratory for Percutaneous Surgery, and his research interests include probabilistic robotics, sensor fusion, medical robotics, and mechatronic systems.
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Lugez, Elodie; Sadjadi, Hossein; Joshi, Chandra P; Hashtrudi-Zaad, Keyvan; Akl, Selim G; Fichtinger, Gabor<\/p>

Field distortion compensation for electromagnetic tracking of ultrasound probes with application in high-dose-rate prostate brachytherapy<\/a> Journal Article<\/span> <\/p>

In: <\/span>Biomedical Physics & Engineering Express, <\/span>vol. 5, <\/span>iss. 3, <\/span>pp. 035026, <\/span>2019<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{fichtinger2019k,
\r\ntitle = {Field distortion compensation for electromagnetic tracking of ultrasound probes with application in high-dose-rate prostate brachytherapy},
\r\nauthor = {Elodie Lugez and Hossein Sadjadi and Chandra P Joshi and Keyvan Hashtrudi-Zaad and Selim G Akl and Gabor Fichtinger},
\r\nurl = {https:\/\/iopscience.iop.org\/article\/10.1088\/2057-1976\/ab12b6\/meta},
\r\nyear  = {2019},
\r\ndate = {2019-01-01},
\r\njournal = {Biomedical Physics & Engineering Express},
\r\nvolume = {5},
\r\nissue = {3},
\r\npages = {035026},
\r\npublisher = {IOP Publishing},
\r\nabstract = {Purpose 
\r\nElectromagnetic (EM) tracking of ultrasound (US) probes has been introduced to expand US imaging capabilities and benefit challenging procedures. However, various instruments\u2014including the US probe itself\u2014may introduce dynamic distortions to the EM field, and compromise the EM measurements. Basic filtering methods, such as those provided by manufacturers, are usually inefficient as they do not allow for field distortion compensation. We propose to use a simultaneous localization and mapping (SLAM) algorithm to track the transrectal US (TRUS) probe while dynamically detect, map, and correct the EM field distortions. 
\r\nMethods 
\r\nCombining the motion model of the tracked probe, the observations made by a few redundant EM sensors, and the field distortions map, the SLAM algorithm relied on an extended Kalman filter (EKF) to estimate the tracking measurements. The SLAM technique was \u2026},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/pre><\/div>
Close<\/a><\/p><\/div>
Purpose 
\r\nElectromagnetic (EM) tracking of ultrasound (US) probes has been introduced to expand US imaging capabilities and benefit challenging procedures. However, various instruments\u2014including the US probe itself\u2014may introduce dynamic distortions to the EM field, and compromise the EM measurements. Basic filtering methods, such as those provided by manufacturers, are usually inefficient as they do not allow for field distortion compensation. We propose to use a simultaneous localization and mapping (SLAM) algorithm to track the transrectal US (TRUS) probe while dynamically detect, map, and correct the EM field distortions. 
\r\nMethods 
\r\nCombining the motion model of the tracked probe, the observations made by a few redundant EM sensors, and the field distortions map, the SLAM algorithm relied on an extended Kalman filter (EKF) to estimate the tracking measurements. The SLAM technique was \u2026<\/div>
Close<\/a><\/p><\/div>