Contour Gradient Tree for Automatic Extraction of Salient Object Surfaces from 3D Imaging Data
Summary :
Isosurface extraction is one of the most popular techniques for visualizing scalar volume data. However, volume data contains infinitely many isosurfaces. Furthermore, a single isosurface might contain many connected components, or contours, with each representing a different object surface. Hence, it is often a tedious and time-consuming manual process to find and extract contours that are interesting to users. This paper describes a novel method for automatically extracting salient contours from volume data. For this purpose, we propose a contour gradient tree (CGT) that contains the information of salient contours and their saliency magnitude. We organize the CGT in a hierarchical way to generate a sequence of contours in saliency order. Our method was applied to various medical datasets. Experimental results show that our method can automatically extract salient contours that represent regions of interest in the data.
- Publication
- IEICE TRANSACTIONS on Information Vol.E98-D No.11 pp.2038-2042
- Publication Date
- 2015/11/01
- Publicized
- 2015/07/31
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2015EDL8137
- Type of Manuscript
- LETTER
- Category
- Computer Graphics
Authors
Bong-Soo SOHN
Chung-Ang University
Keyword
Latest Issue
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Bong-Soo SOHN, "Contour Gradient Tree for Automatic Extraction of Salient Object Surfaces from 3D Imaging Data" in IEICE TRANSACTIONS on Information,
vol. E98-D, no. 11, pp. 2038-2042, November 2015, doi: 10.1587/transinf.2015EDL8137.
Abstract: Isosurface extraction is one of the most popular techniques for visualizing scalar volume data. However, volume data contains infinitely many isosurfaces. Furthermore, a single isosurface might contain many connected components, or contours, with each representing a different object surface. Hence, it is often a tedious and time-consuming manual process to find and extract contours that are interesting to users. This paper describes a novel method for automatically extracting salient contours from volume data. For this purpose, we propose a contour gradient tree (CGT) that contains the information of salient contours and their saliency magnitude. We organize the CGT in a hierarchical way to generate a sequence of contours in saliency order. Our method was applied to various medical datasets. Experimental results show that our method can automatically extract salient contours that represent regions of interest in the data.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDL8137/_p
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@ARTICLE{e98-d_11_2038,
author={Bong-Soo SOHN, },
journal={IEICE TRANSACTIONS on Information},
title={Contour Gradient Tree for Automatic Extraction of Salient Object Surfaces from 3D Imaging Data},
year={2015},
volume={E98-D},
number={11},
pages={2038-2042},
abstract={Isosurface extraction is one of the most popular techniques for visualizing scalar volume data. However, volume data contains infinitely many isosurfaces. Furthermore, a single isosurface might contain many connected components, or contours, with each representing a different object surface. Hence, it is often a tedious and time-consuming manual process to find and extract contours that are interesting to users. This paper describes a novel method for automatically extracting salient contours from volume data. For this purpose, we propose a contour gradient tree (CGT) that contains the information of salient contours and their saliency magnitude. We organize the CGT in a hierarchical way to generate a sequence of contours in saliency order. Our method was applied to various medical datasets. Experimental results show that our method can automatically extract salient contours that represent regions of interest in the data.},
keywords={},
doi={10.1587/transinf.2015EDL8137},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Contour Gradient Tree for Automatic Extraction of Salient Object Surfaces from 3D Imaging Data
T2 - IEICE TRANSACTIONS on Information
SP - 2038
EP - 2042
AU - Bong-Soo SOHN
PY - 2015
DO - 10.1587/transinf.2015EDL8137
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2015
AB - Isosurface extraction is one of the most popular techniques for visualizing scalar volume data. However, volume data contains infinitely many isosurfaces. Furthermore, a single isosurface might contain many connected components, or contours, with each representing a different object surface. Hence, it is often a tedious and time-consuming manual process to find and extract contours that are interesting to users. This paper describes a novel method for automatically extracting salient contours from volume data. For this purpose, we propose a contour gradient tree (CGT) that contains the information of salient contours and their saliency magnitude. We organize the CGT in a hierarchical way to generate a sequence of contours in saliency order. Our method was applied to various medical datasets. Experimental results show that our method can automatically extract salient contours that represent regions of interest in the data.
ER -
English
