3D segmentation of thyroid ultrasound images using active contours

In this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to...

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Main Authors: Poudel Prabal, Hansen Christian, Sprung Julian, Friebe Michael
Format: Article
Language:English
Published: De Gruyter 2016-09-01
Series:Current Directions in Biomedical Engineering
Subjects:
Online Access:https://doi.org/10.1515/cdbme-2016-0103
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spelling doaj-7fc17f94f5c8489bb013bee9a9cc46562021-09-06T19:19:23ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042016-09-012146747010.1515/cdbme-2016-0103cdbme-2016-01033D segmentation of thyroid ultrasound images using active contoursPoudel Prabal0Hansen Christian1Sprung Julian2Friebe Michael3University of BonnOtto-von-Guericke University MagdeburgOtto-von-Guericke University MagdeburgOtto-von-Guericke University MagdeburgIn this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to segment the thyroid in each of the 2D images. Finally, all the segmented thyroid images are passed to a 3D reconstruction algorithm to obtain a 3D model of the thyroid. We obtained an average segmentation accuracy of 86.7% in six datasets with a total of 703 images.https://doi.org/10.1515/cdbme-2016-0103active contours without edgessegmentationthyroid glandultrasound
collection DOAJ
language English
format Article
sources DOAJ
author Poudel Prabal
Hansen Christian
Sprung Julian
Friebe Michael
spellingShingle Poudel Prabal
Hansen Christian
Sprung Julian
Friebe Michael
3D segmentation of thyroid ultrasound images using active contours
Current Directions in Biomedical Engineering
active contours without edges
segmentation
thyroid gland
ultrasound
author_facet Poudel Prabal
Hansen Christian
Sprung Julian
Friebe Michael
author_sort Poudel Prabal
title 3D segmentation of thyroid ultrasound images using active contours
title_short 3D segmentation of thyroid ultrasound images using active contours
title_full 3D segmentation of thyroid ultrasound images using active contours
title_fullStr 3D segmentation of thyroid ultrasound images using active contours
title_full_unstemmed 3D segmentation of thyroid ultrasound images using active contours
title_sort 3d segmentation of thyroid ultrasound images using active contours
publisher De Gruyter
series Current Directions in Biomedical Engineering
issn 2364-5504
publishDate 2016-09-01
description In this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to segment the thyroid in each of the 2D images. Finally, all the segmented thyroid images are passed to a 3D reconstruction algorithm to obtain a 3D model of the thyroid. We obtained an average segmentation accuracy of 86.7% in six datasets with a total of 703 images.
topic active contours without edges
segmentation
thyroid gland
ultrasound
url https://doi.org/10.1515/cdbme-2016-0103
work_keys_str_mv AT poudelprabal 3dsegmentationofthyroidultrasoundimagesusingactivecontours
AT hansenchristian 3dsegmentationofthyroidultrasoundimagesusingactivecontours
AT sprungjulian 3dsegmentationofthyroidultrasoundimagesusingactivecontours
AT friebemichael 3dsegmentationofthyroidultrasoundimagesusingactivecontours
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