Structural flow smoothing for shape interpolation

Ashish Doshi; Adrian G. Bors

Structural flow smoothing for shape interpolation

Computer Science

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

Abstract

This paper presents a comparative study of robust diffusion algorithms when used for smoothing structural fields applied in volumetric image interpolation. The input data consists of a set of parallel and equidistant slices which are considered sparsely located along a central axis. The structural flows are constructed using the dual directional block matching algorithm (DBMA). Two vectorial flows are modelled in both directions along the central axis, using the correlation between blocks of pixels from successive slices. As with most block matching algorithms, this method is susceptible to noise and the resulting vector fields contain outliers. A methodology that combines diffusion and robust statistics in order to smooth the dual structural flow is proposed. Consequently, new slices are interpolated in between the existing slices, according to the smoothed vector fields. The set of algorithms is applied in volumetric medical images.

Original language	English
Title of host publication	18th International Conference on Pattern Recognition, Vol 3, Proceedings
Editors	YY Tang, SP Wang, G Lorette, DS Yeung, H Yan
Place of Publication	LOS ALAMITOS
Publisher	IEEE Computer Society
Pages	11-14
Number of pages	4
ISBN (Print)	0-7695-2521-0
Publication status	Published - 2006
Event	18th International Conference on Pattern Recognition (ICPR 2006) - Hong Kong Duration: 20 Aug 2006 → 24 Aug 2006

Conference

Conference	18th International Conference on Pattern Recognition (ICPR 2006)
City	Hong Kong
Period	20/08/06 → 24/08/06

Keywords

OPTICAL-FLOW
ANISOTROPIC DIFFUSION
IMAGE INTERPOLATION
RECONSTRUCTION

Cite this

@inproceedings{e4722bcf1ff541279066d01da6fe1e97,

title = "Structural flow smoothing for shape interpolation",

abstract = "This paper presents a comparative study of robust diffusion algorithms when used for smoothing structural fields applied in volumetric image interpolation. The input data consists of a set of parallel and equidistant slices which are considered sparsely located along a central axis. The structural flows are constructed using the dual directional block matching algorithm (DBMA). Two vectorial flows are modelled in both directions along the central axis, using the correlation between blocks of pixels from successive slices. As with most block matching algorithms, this method is susceptible to noise and the resulting vector fields contain outliers. A methodology that combines diffusion and robust statistics in order to smooth the dual structural flow is proposed. Consequently, new slices are interpolated in between the existing slices, according to the smoothed vector fields. The set of algorithms is applied in volumetric medical images.",

keywords = "OPTICAL-FLOW, ANISOTROPIC DIFFUSION, IMAGE INTERPOLATION, RECONSTRUCTION",

author = "Ashish Doshi and Bors, {Adrian G.}",

year = "2006",

language = "English",

isbn = "0-7695-2521-0",

pages = "11--14",

editor = "YY Tang and SP Wang and G Lorette and DS Yeung and H Yan",

booktitle = "18th International Conference on Pattern Recognition, Vol 3, Proceedings",

publisher = "IEEE Computer Society",

address = "United States",

note = "18th International Conference on Pattern Recognition (ICPR 2006) ; Conference date: 20-08-2006 Through 24-08-2006",

}

TY - GEN

T1 - Structural flow smoothing for shape interpolation

AU - Doshi, Ashish

AU - Bors, Adrian G.

PY - 2006

Y1 - 2006

N2 - This paper presents a comparative study of robust diffusion algorithms when used for smoothing structural fields applied in volumetric image interpolation. The input data consists of a set of parallel and equidistant slices which are considered sparsely located along a central axis. The structural flows are constructed using the dual directional block matching algorithm (DBMA). Two vectorial flows are modelled in both directions along the central axis, using the correlation between blocks of pixels from successive slices. As with most block matching algorithms, this method is susceptible to noise and the resulting vector fields contain outliers. A methodology that combines diffusion and robust statistics in order to smooth the dual structural flow is proposed. Consequently, new slices are interpolated in between the existing slices, according to the smoothed vector fields. The set of algorithms is applied in volumetric medical images.

AB - This paper presents a comparative study of robust diffusion algorithms when used for smoothing structural fields applied in volumetric image interpolation. The input data consists of a set of parallel and equidistant slices which are considered sparsely located along a central axis. The structural flows are constructed using the dual directional block matching algorithm (DBMA). Two vectorial flows are modelled in both directions along the central axis, using the correlation between blocks of pixels from successive slices. As with most block matching algorithms, this method is susceptible to noise and the resulting vector fields contain outliers. A methodology that combines diffusion and robust statistics in order to smooth the dual structural flow is proposed. Consequently, new slices are interpolated in between the existing slices, according to the smoothed vector fields. The set of algorithms is applied in volumetric medical images.

KW - OPTICAL-FLOW

KW - ANISOTROPIC DIFFUSION

KW - IMAGE INTERPOLATION

KW - RECONSTRUCTION

M3 - Conference contribution

SN - 0-7695-2521-0

SP - 11

EP - 14

BT - 18th International Conference on Pattern Recognition, Vol 3, Proceedings

A2 - Tang, YY

A2 - Wang, SP

A2 - Lorette, G

A2 - Yeung, DS

A2 - Yan, H

PB - IEEE Computer Society

CY - LOS ALAMITOS

T2 - 18th International Conference on Pattern Recognition (ICPR 2006)

Y2 - 20 August 2006 through 24 August 2006

ER -