{"id":2365,"date":"2024-03-09T15:50:32","date_gmt":"2024-03-09T15:50:32","guid":{"rendered":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/ehasn-dehghan\/"},"modified":"2024-03-09T15:50:32","modified_gmt":"2024-03-09T15:50:32","slug":"ehasn-dehghan","status":"publish","type":"qsc_member","link":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/ehasn-dehghan\/","title":{"rendered":"Ehasn Dehghan"},"content":{"rendered":"
\n
\n\t\t\"\"\n\t<\/div>\n
\n
\n

Ehasn Dehghan<\/h1>\n<\/div>\n
Postdoctoral Fellow<\/div>\n
School of Computing<\/div>\n
Queen’s University<\/div>\n
Member from 2010<\/em> to 2012<\/em><\/div>\n
\n
\n\t\t\t<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n
\n
<\/a><\/form>

Dehghan, Ehsan; Le, Yi; Lee, Junghoon; Song, Danny Y; Fichtinger, Gabor; Prince, Jerry L.<\/p>

CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION<\/a> Conference<\/span> <\/p>

IEEE Int. Symp on Biomedical Imaging, <\/span>2016<\/span>.<\/p>

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

@conference{Dehghan2016,
\r\ntitle = {CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION},
\r\nauthor = {Ehsan Dehghan and Yi Le and Junghoon Lee and Danny Y Song and Gabor Fichtinger and Jerry L. Prince},
\r\nurl = {https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Ehsan_ISBI_2016.pdf},
\r\nyear  = {2016},
\r\ndate = {2016-04-01},
\r\nurldate = {2016-04-01},
\r\nbooktitle = {IEEE Int. Symp on Biomedical Imaging},
\r\npages = {625-628},
\r\nabstract = {<p>Postoperative evaluation of prostate brachytherapy is typically<br \/> 
\r\nperformed using CT, which does not have sufficient<br \/> 
\r\nsoft tissue contrast for accurate anatomy delineation. MR-CT<br \/> 
\r\nfusion enables more accurate localization of both anatomy<br \/> 
\r\nand implanted radioactive seeds, and hence, improves the<br \/> 
\r\naccuracy of postoperative dosimetry. We propose a method<br \/> 
\r\nfor automatic registration of MR and CT images without a<br \/> 
\r\nneed for manual initialization. Our registration method employs<br \/> 
\r\na point-to-volume registration scheme during which<br \/> 
\r\nlocalized seeds in the CT images, produced by commercial<br \/> 
\r\ntreatment planning systems as part of the standard of care,<br \/> 
\r\nare rigidly registered to preprocessed MRI images. We tested<br \/> 
\r\nour algorithm on ten patient data sets and achieved an overall<br \/> 
\r\nregistration error of 1.6 \u00b1 0.8mm with a running time of less<br \/> 
\r\nthan 20s. With high registration accuracy and computational<br \/> 
\r\nspeed, and no need for manual intervention, our method has<br \/> 
\r\nthe potential to be employed in clinical applications.<\/p>},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {conference}
\r\n}
\r\n<\/pre><\/div>
Close<\/a><\/p><\/div>
<p>Postoperative evaluation of prostate brachytherapy is typically<br \/> 
\r\nperformed using CT, which does not have sufficient<br \/> 
\r\nsoft tissue contrast for accurate anatomy delineation. MR-CT<br \/> 
\r\nfusion enables more accurate localization of both anatomy<br \/> 
\r\nand implanted radioactive seeds, and hence, improves the<br \/> 
\r\naccuracy of postoperative dosimetry. We propose a method<br \/> 
\r\nfor automatic registration of MR and CT images without a<br \/> 
\r\nneed for manual initialization. Our registration method employs<br \/> 
\r\na point-to-volume registration scheme during which<br \/> 
\r\nlocalized seeds in the CT images, produced by commercial<br \/> 
\r\ntreatment planning systems as part of the standard of care,<br \/> 
\r\nare rigidly registered to preprocessed MRI images. We tested<br \/> 
\r\nour algorithm on ten patient data sets and achieved an overall<br \/> 
\r\nregistration error of 1.6 \u00b1 0.8mm with a running time of less<br \/> 
\r\nthan 20s. With high registration accuracy and computational<br \/> 
\r\nspeed, and no need for manual intervention, our method has<br \/> 
\r\nthe potential to be employed in clinical applications.<\/p><\/div>
Close<\/a><\/p><\/div>