{"id":2392,"date":"2024-03-09T16:26:42","date_gmt":"2024-03-09T16:26:42","guid":{"rendered":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/shahrokh-kamali\/"},"modified":"2024-03-09T16:26:42","modified_gmt":"2024-03-09T16:26:42","slug":"shahrokh-kamali","status":"publish","type":"qsc_member","link":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/shahrokh-kamali\/","title":{"rendered":"Shahrokh Kamali"},"content":{"rendered":"<div class=\"wp-block-columns is-layout-flex wp-block-columns-is-layout-flex qsc-member-single-core-info-container\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow qsc-member-single-photo-column\">\n\t\t<img loading=\"lazy\" decoding=\"async\" width=\"250\" height=\"188\" src=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/03\/ShahrokhKamali.jpg\" class=\"qsc-member-single-photo wp-post-image\" alt=\"\" srcset=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/03\/ShahrokhKamali.jpg 480w, https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/03\/ShahrokhKamali-300x225.jpg 300w\" sizes=\"auto, (max-width: 250px) 100vw, 250px\" \/>\n\t<\/div>\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow qsc-member-single-info-column\">\n<div class=\"qsc-member-name\">\n<h1>Shahrokh Kamali<\/h1>\n<\/div>\n<div class=\"qsc-member-position\">PhD Student<\/div>\n<div class=\"qsc-member-department\"><\/div>\n<div class=\"qsc-member-organization\">Dalhousie University<\/div>\n<div class=\"qsc-member-date-range\">Member from <em>2014<\/em> to <em>present<\/em><\/div>\n<div class=\"qsc-member-contact\">\n<div class=\"qsc-member-socials\">\n\t\t\t<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n<div class=\"qsc-member-bio\">\n\tShahrokh received his BSc in Electrical Engineering from Shiraz University, Shiraz, Iran and MASc in Electrical Engineering from Dalhousie University. He was a PhD student at Dalhousie University and a visiting student at the Perk Lab.<br \/>\n<div class=\"teachpress_pub_list\"><form name=\"tppublistform\" method=\"get\"><a name=\"tppubs\" id=\"tppubs\"><\/a><\/form><div class=\"teachpress_publication_list\"><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Pinter, Csaba;  Travers, Bryan;  Baum, Zachary M C;  Kamali, Shahrokh;  Ungi, Tamas;  Lasso, Andras;  Church, Ben;  Fichtinger, Gabor<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" href=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Pinter2018.pdf\" title=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Pinter2018.pdf\" target=\"blank\">Real-time transverse process detection in ultrasound<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">SPIE Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, <\/span><span class=\"tp_pub_additional_address\">Houston, Texas, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_99\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('99','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_99\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('99','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_99\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Pinter2018,<br \/>\r\ntitle = {Real-time transverse process detection in ultrasound},<br \/>\r\nauthor = {Csaba Pinter and Bryan Travers and Zachary M C Baum and Shahrokh Kamali and Tamas Ungi and Andras Lasso and Ben Church and Gabor Fichtinger},<br \/>\r\nurl = {https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Pinter2018.pdf},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-03-01},<br \/>\r\nurldate = {2018-03-01},<br \/>\r\nbooktitle = {SPIE Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling},<br \/>\r\naddress = {Houston, Texas},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('99','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_99\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Pinter2018.pdf\" title=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Pinter2018[...]\" target=\"_blank\">https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Pinter2018[...]<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('99','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Kamali, Shahrokh;  Ungi, Tamas;  Lasso, Andras;  Yan, Christina;  Lougheed, Matthew;  Fichtinger, Gabor<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" href=\"https:\/\/dx.doi.org\/10.1117\/12.2256007\" title=\"Localization of the transverse processes in ultrasound for spinal curvature measurement\" target=\"blank\">Localization of the transverse processes in ultrasound for spinal curvature measurement<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">SPIE Medical Imaging, <\/span><span class=\"tp_pub_additional_volume\">vol. 10135, <\/span><span class=\"tp_pub_additional_year\">2017<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_127\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('127','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_127\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('127','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_127\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('127','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_127\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Kamali2017a,<br \/>\r\ntitle = {Localization of the transverse processes in ultrasound for spinal curvature measurement},<br \/>\r\nauthor = {Shahrokh Kamali and Tamas Ungi and Andras Lasso and Christina Yan and Matthew Lougheed and Gabor Fichtinger},<br \/>\r\nurl = {http:\/\/proceedings.spiedigitallibrary.org\/proceeding.aspx?articleid=2615387<br \/>\r\nhttps:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Kamali2017a.pdf},<br \/>\r\ndoi = {10.1117\/12.2256007},<br \/>\r\nyear  = {2017},<br \/>\r\ndate = {2017-02-01},<br \/>\r\nurldate = {2017-02-01},<br \/>\r\nbooktitle = {SPIE Medical Imaging},<br \/>\r\nvolume = {10135},<br \/>\r\npages = {101350I-101350I-7},<br \/>\r\nabstract = {&lt;p&gt;PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks such as transverse processes, but as bones have reduced visibility in ultrasound imaging, skeletal landmarks are typically segmented manually, which is an exceedingly laborious and long process. We propose an automatic algorithm to segment and localize the surface of bony areas in the transverse process for scoliosis in ultrasound.METHODS: The algorithm uses cascade of filters to remove low intensity pixels, smooth the image and detect bony edges. By applying first differentiation, candidate bony areas are classified. The average intensity under each area has a correlation with the possibility of a shadow, and areas with strong shadow are kept for bone segmentation. The segmented images are used to reconstruct a 3-D volume to represent the whole spinal structure around the transverse processes. RESULTS: A comparison between the manual ground truth segmentation and the automatic algorithm in 50 images showed 0.17 mm average difference. The time to process all 1,938 images was about 37 Sec. (0.0191 Sec. \/ Image), including reading the original sequence file.CONCLUSION: Initial experiments showed the algorithm to be sufficiently accurate and fast for segmentation transverse processes in ultrasound for spinal curvature measurement. An extensive evaluation of the method is currently underway on images from a larger patient cohort and using multiple observers in producing ground truth segmentation.&lt;\/p&gt;},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('127','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_127\" style=\"display:none;\"><div class=\"tp_abstract_entry\">&lt;p&gt;PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks such as transverse processes, but as bones have reduced visibility in ultrasound imaging, skeletal landmarks are typically segmented manually, which is an exceedingly laborious and long process. We propose an automatic algorithm to segment and localize the surface of bony areas in the transverse process for scoliosis in ultrasound.METHODS: The algorithm uses cascade of filters to remove low intensity pixels, smooth the image and detect bony edges. By applying first differentiation, candidate bony areas are classified. The average intensity under each area has a correlation with the possibility of a shadow, and areas with strong shadow are kept for bone segmentation. The segmented images are used to reconstruct a 3-D volume to represent the whole spinal structure around the transverse processes. RESULTS: A comparison between the manual ground truth segmentation and the automatic algorithm in 50 images showed 0.17 mm average difference. The time to process all 1,938 images was about 37 Sec. (0.0191 Sec. \/ Image), including reading the original sequence file.CONCLUSION: Initial experiments showed the algorithm to be sufficiently accurate and fast for segmentation transverse processes in ultrasound for spinal curvature measurement. An extensive evaluation of the method is currently underway on images from a larger patient cohort and using multiple observers in producing ground truth segmentation.&lt;\/p&gt;<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('127','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_127\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/proceedings.spiedigitallibrary.org\/proceeding.aspx?articleid=2615387\" title=\"http:\/\/proceedings.spiedigitallibrary.org\/proceeding.aspx?articleid=2615387\" target=\"_blank\">http:\/\/proceedings.spiedigitallibrary.org\/proceeding.aspx?articleid=2615387<\/a><\/li><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Kamali2017a.pdf\" title=\"https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Kamali2017[...]\" target=\"_blank\">https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Kamali2017[...]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1117\/12.2256007\" title=\"Follow DOI:10.1117\/12.2256007\" target=\"_blank\">doi:10.1117\/12.2256007<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('127','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><\/div><\/div>\n<\/div>\n","protected":false},"featured_media":1674,"template":"","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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Martin","author_link":"https:\/\/labs.cs.queensu.ca\/perklab\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Shahrokh Kamali PhD Student Dalhousie University Member from 2014 to present Shahrokh received his BSc in Electrical Engineering from Shiraz University, Shiraz, Iran and MASc in Electrical Engineering from Dalhousie University. He was a PhD student at Dalhousie University and a visiting student at the Perk Lab. Pinter, Csaba; Travers, Bryan; Baum, Zachary M C;&hellip;","_links":{"self":[{"href":"https:\/\/labs.cs.queensu.ca\/perklab\/wp-json\/wp\/v2\/qsc_member\/2392","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/labs.cs.queensu.ca\/perklab\/wp-json\/wp\/v2\/qsc_member"}],"about":[{"href":"https:\/\/labs.cs.queensu.ca\/perklab\/wp-json\/wp\/v2\/types\/qsc_member"}],"version-history":[{"count":0,"href":"https:\/\/labs.cs.queensu.ca\/perklab\/wp-json\/wp\/v2\/qsc_member\/2392\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/labs.cs.queensu.ca\/perklab\/wp-json\/wp\/v2\/media\/1674"}],"wp:attachment":[{"href":"https:\/\/labs.cs.queensu.ca\/perklab\/wp-json\/wp\/v2\/media?parent=2392"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}