Longitudinal assessment of brain tumors using a repeatable prior-based segmentation

L. Weizman; L. Joskowicz; L. Ben-Sira; B. Shofty; S. Constantini; D. Ben-Bashat

doi:https://doi.org/10.1109/ISBI.2011.5872740

Longitudinal assessment of brain tumors using a repeatable prior-based segmentation

L. Weizman, L. Joskowicz, L. Ben-Sira, B. Shofty, S. Constantini, D. Ben-Bashat

Tel Aviv University, The Hebrew University of Jerusalem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents an automatic method for a repeatable, prior-based segmentation and classification of brain tumors in longitudinal MR scans. The method is designed to overcome the inter/intra observer variability and to provide a repeatable delineation of the tumor boundaries in a set of follow-up scans of the same patient. The method effectively incorporates manual delineation of the first scan in the time-series to segment and classify a series of follow-up scans. Experimental results on 16 datasets yield a mean surface distance error of 0.22mm and a mean volume overlap difference of 12.34% as compared to manual segmentation by an expert radiologist.

Original language	English
Title of host publication	2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI'11
Pages	1733-1736
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2011.5872740
State	Published - 2011
Event	2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States Duration: 30 Mar 2011 → 2 Apr 2011

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging

Conference

Conference	2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
Country/Territory	United States
City	Chicago, IL
Period	30/03/11 → 2/04/11

Keywords

MRI
brain tumor
follow-up
segmentation

All Science Journal Classification (ASJC) codes

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

https://doi.org/10.1109/ISBI.2011.5872740

Cite this

Weizman, L., Joskowicz, L., Ben-Sira, L., Shofty, B., Constantini, S., & Ben-Bashat, D. (2011). Longitudinal assessment of brain tumors using a repeatable prior-based segmentation. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 (pp. 1733-1736). Article 5872740 (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2011.5872740

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abstract = "This paper presents an automatic method for a repeatable, prior-based segmentation and classification of brain tumors in longitudinal MR scans. The method is designed to overcome the inter/intra observer variability and to provide a repeatable delineation of the tumor boundaries in a set of follow-up scans of the same patient. The method effectively incorporates manual delineation of the first scan in the time-series to segment and classify a series of follow-up scans. Experimental results on 16 datasets yield a mean surface distance error of 0.22mm and a mean volume overlap difference of 12.34% as compared to manual segmentation by an expert radiologist.",

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author = "L. Weizman and L. Joskowicz and L. Ben-Sira and B. Shofty and S. Constantini and D. Ben-Bashat",

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Weizman, L, Joskowicz, L, Ben-Sira, L, Shofty, B, Constantini, S & Ben-Bashat, D 2011, Longitudinal assessment of brain tumors using a repeatable prior-based segmentation. in 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11., 5872740, Proceedings - International Symposium on Biomedical Imaging, pp. 1733-1736, 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11, Chicago, IL, United States, 30/03/11. https://doi.org/10.1109/ISBI.2011.5872740

Longitudinal assessment of brain tumors using a repeatable prior-based segmentation. / Weizman, L.; Joskowicz, L.; Ben-Sira, L. et al.
2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 1733-1736 5872740 (Proceedings - International Symposium on Biomedical Imaging).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents an automatic method for a repeatable, prior-based segmentation and classification of brain tumors in longitudinal MR scans. The method is designed to overcome the inter/intra observer variability and to provide a repeatable delineation of the tumor boundaries in a set of follow-up scans of the same patient. The method effectively incorporates manual delineation of the first scan in the time-series to segment and classify a series of follow-up scans. Experimental results on 16 datasets yield a mean surface distance error of 0.22mm and a mean volume overlap difference of 12.34% as compared to manual segmentation by an expert radiologist.

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KW - brain tumor

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Weizman L, Joskowicz L, Ben-Sira L, Shofty B, Constantini S, Ben-Bashat D. Longitudinal assessment of brain tumors using a repeatable prior-based segmentation. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 1733-1736. 5872740. (Proceedings - International Symposium on Biomedical Imaging). doi: https://doi.org/10.1109/ISBI.2011.5872740

Longitudinal assessment of brain tumors using a repeatable prior-based segmentation

Abstract

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Keywords

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