Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Weighted 3D volume reconstruction from series of slice data using a modified Allen-Cahn equationopen access

Authors
Li, YibaoSong, XinKwak, SoobinKim, Junseok
Issue Date
12월-2022
Publisher
ELSEVIER SCI LTD
Keywords
Shape transformation; 3D volume reconstruction; Allen-Cahn equation
Citation
PATTERN RECOGNITION, v.132
Indexed
SCIE
SCOPUS
Journal Title
PATTERN RECOGNITION
Volume
132
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/146484
DOI
10.1016/j.patcog.2022.108914
ISSN
0031-3203
Abstract
In this study, we develop a fast and accurate computational method for a weighted three-dimensional (3D) volume reconstruction from a series of slice data using a phase-field model. The proposed method is based on a modified Allen-Cahn (AC) equation with a fidelity term. The algorithm automatically gener-ates the necessary slices between the given slices by solving the governing equation. To reconstruct a 3D volume, we first set a source slice and target slice. Next, we set the source slice as the initial condition and the target slice as the fidelity function. Finally, we retain the numerical solutions during an evolution as intermediate slices between the source and target slices. There are two criteria for choosing the in-termediate slice: One is based on the area of the symmetric difference between the phase-field solution and the target and the other is based on the change of the phase-field solution relative to the area of the target. We use the weighted average of the two criteria. To validate the efficiency and accuracy of the proposed numerical algorithm, several computational experiments are conducted. Computational test results confirm the superior performance of the proposed algorithm.(c) 2022 Elsevier Ltd. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Science > Department of Mathematics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Jun seok photo

Kim, Jun seok
이과대학 (수학과)
Read more

Altmetrics

Total Views & Downloads

BROWSE