Feature based rendering for 2D/3D partial volume segmentation datasets

Zigang Wang; Zhengrong Liang

doi:10.1117/12.466978

Feature based rendering for 2D/3D partial volume segmentation datasets

Zigang Wang
, Zhengrong Liang

Radiology

Stony Brook University

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

In this paper, a new feature based rendering algorithm for partial volume is presented. This algorithm utilizes both surface and volume information for the rendering of the partial volume segmentation data with associated features. First principal directions are extracted from the partial volume segmentation dataset to construct a feature vector dataset. Using the improved LIC (line integral convolution) algorithm, our rendering algorithm can integrate the feature dataset into the traditional volume rendering process. Combining the features and the traditional volume rendering, the partial volume could be visualized clearly. This can result in an improved diagnosis in clinic, because the partial volume quantities carry very rich diagnostic information.

Original language	English
Pages (from-to)	681-687
Number of pages	7
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	4681
DOIs	https://doi.org/10.1117/12.466978
State	Published - 2002
Event	Medical Imaging 2002 Visualization, Image-Guided Procedures and Display - San Diego, CA, United States Duration: Feb 24 2002 → Feb 26 2002

Keywords

And Visualization
Line Integral Convolution
Partial Volume Segmentation
Volume Rendering

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10.1117/12.466978

Cite this

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title = "Feature based rendering for 2D/3D partial volume segmentation datasets",

abstract = "In this paper, a new feature based rendering algorithm for partial volume is presented. This algorithm utilizes both surface and volume information for the rendering of the partial volume segmentation data with associated features. First principal directions are extracted from the partial volume segmentation dataset to construct a feature vector dataset. Using the improved LIC (line integral convolution) algorithm, our rendering algorithm can integrate the feature dataset into the traditional volume rendering process. Combining the features and the traditional volume rendering, the partial volume could be visualized clearly. This can result in an improved diagnosis in clinic, because the partial volume quantities carry very rich diagnostic information.",

keywords = "And Visualization, Line Integral Convolution, Partial Volume Segmentation, Volume Rendering",

author = "Zigang Wang and Zhengrong Liang",

year = "2002",

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language = "English",

volume = "4681",

pages = "681--687",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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note = "Medical Imaging 2002 Visualization, Image-Guided Procedures and Display ; Conference date: 24-02-2002 Through 26-02-2002",

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TY - JOUR

T1 - Feature based rendering for 2D/3D partial volume segmentation datasets

AU - Wang, Zigang

AU - Liang, Zhengrong

PY - 2002

Y1 - 2002

N2 - In this paper, a new feature based rendering algorithm for partial volume is presented. This algorithm utilizes both surface and volume information for the rendering of the partial volume segmentation data with associated features. First principal directions are extracted from the partial volume segmentation dataset to construct a feature vector dataset. Using the improved LIC (line integral convolution) algorithm, our rendering algorithm can integrate the feature dataset into the traditional volume rendering process. Combining the features and the traditional volume rendering, the partial volume could be visualized clearly. This can result in an improved diagnosis in clinic, because the partial volume quantities carry very rich diagnostic information.

AB - In this paper, a new feature based rendering algorithm for partial volume is presented. This algorithm utilizes both surface and volume information for the rendering of the partial volume segmentation data with associated features. First principal directions are extracted from the partial volume segmentation dataset to construct a feature vector dataset. Using the improved LIC (line integral convolution) algorithm, our rendering algorithm can integrate the feature dataset into the traditional volume rendering process. Combining the features and the traditional volume rendering, the partial volume could be visualized clearly. This can result in an improved diagnosis in clinic, because the partial volume quantities carry very rich diagnostic information.

KW - And Visualization

KW - Line Integral Convolution

KW - Partial Volume Segmentation

KW - Volume Rendering

UR - https://www.scopus.com/pages/publications/0036060937

U2 - 10.1117/12.466978

DO - 10.1117/12.466978

M3 - Conference article

AN - SCOPUS:0036060937

SN - 0277-786X

VL - 4681

SP - 681

EP - 687

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Medical Imaging 2002 Visualization, Image-Guided Procedures and Display

Y2 - 24 February 2002 through 26 February 2002

ER -

Feature based rendering for 2D/3D partial volume segmentation datasets

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Keywords

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