Interactive level set segmentation for image-guided therapy
Image-guided therapy procedures require the patient to remain still throughout the image acquisition, data analysis and therapy. This imposes a tight time constraint on the over-all process. Automatic extraction of the pathological regions prior to the therapy can be faster than the customary manual...
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Language: | en_US |
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Institute of Electrical and Electronics Engineers
2010
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Online Access: | http://hdl.handle.net/1721.1/55357 |
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author | Kiryati, Nahum Ben-Zadok, Nir Riklin-Raviv, Tammy |
author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Kiryati, Nahum Ben-Zadok, Nir Riklin-Raviv, Tammy |
author_sort | Kiryati, Nahum |
collection | MIT |
description | Image-guided therapy procedures require the patient to remain still throughout the image acquisition, data analysis and therapy. This imposes a tight time constraint on the over-all process. Automatic extraction of the pathological regions prior to the therapy can be faster than the customary manual segmentation performed by the physician. However, the image data alone is usually not sufficient for reliable and unambiguous computerized segmentation. Thus, the oversight of an experienced physician remains mandatory. We present a novel segmentation framework, that allows user feedback. A few mouse-clicks of the user, discrete in nature, are represented as a continuous energy term that is incorporated into a level-set functional. We demonstrate the proposed method on MR scans of uterine fibroids acquired prior to focused ultrasound ablation treatment. The experiments show that with a minimal user input, automatic segmentation results become practically identical to manual expert segmentation. |
first_indexed | 2024-09-23T10:53:28Z |
format | Article |
id | mit-1721.1/55357 |
institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T10:53:28Z |
publishDate | 2010 |
publisher | Institute of Electrical and Electronics Engineers |
record_format | dspace |
spelling | mit-1721.1/553572022-09-30T23:45:52Z Interactive level set segmentation for image-guided therapy Kiryati, Nahum Ben-Zadok, Nir Riklin-Raviv, Tammy Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Riklin-Raviv, Tammy Riklin-Raviv, Tammy User interaction MR scans segmentation Level-set framework Image guided therapy Image-guided therapy procedures require the patient to remain still throughout the image acquisition, data analysis and therapy. This imposes a tight time constraint on the over-all process. Automatic extraction of the pathological regions prior to the therapy can be faster than the customary manual segmentation performed by the physician. However, the image data alone is usually not sufficient for reliable and unambiguous computerized segmentation. Thus, the oversight of an experienced physician remains mandatory. We present a novel segmentation framework, that allows user feedback. A few mouse-clicks of the user, discrete in nature, are represented as a continuous energy term that is incorporated into a level-set functional. We demonstrate the proposed method on MR scans of uterine fibroids acquired prior to focused ultrasound ablation treatment. The experiments show that with a minimal user input, automatic segmentation results become practically identical to manual expert segmentation. A.M.N. Foundation for the Advancement of Science, Art and Culture in Israel 2010-05-28T20:36:48Z 2010-05-28T20:36:48Z 2009-08 Article http://purl.org/eprint/type/ConferencePaper 978-1-4244-3932-4 1945-7928 INSPEC Accession Number: 10814218 http://hdl.handle.net/1721.1/55357 Ben-Zadok, N., T. Riklin-Raviv, and N. Kiryati. “Interactive level set segmentation for image-guided therapy.” Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on. 2009. 1079-1082. ©2009 Institute of Electrical and Electronics Engineers. en_US http://dx.doi.org/10.1109/ISBI.2009.5193243 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009. ISBI '09 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers IEEE |
spellingShingle | User interaction MR scans segmentation Level-set framework Image guided therapy Kiryati, Nahum Ben-Zadok, Nir Riklin-Raviv, Tammy Interactive level set segmentation for image-guided therapy |
title | Interactive level set segmentation for image-guided therapy |
title_full | Interactive level set segmentation for image-guided therapy |
title_fullStr | Interactive level set segmentation for image-guided therapy |
title_full_unstemmed | Interactive level set segmentation for image-guided therapy |
title_short | Interactive level set segmentation for image-guided therapy |
title_sort | interactive level set segmentation for image guided therapy |
topic | User interaction MR scans segmentation Level-set framework Image guided therapy |
url | http://hdl.handle.net/1721.1/55357 |
work_keys_str_mv | AT kiryatinahum interactivelevelsetsegmentationforimageguidedtherapy AT benzadoknir interactivelevelsetsegmentationforimageguidedtherapy AT riklinravivtammy interactivelevelsetsegmentationforimageguidedtherapy |