Robust diffusion of structural flows for volumetric image interpolation

Ashish Doshi; Adrian G. Bors

Robust diffusion of structural flows for volumetric image interpolation

Computer Science

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

Abstract

In this paper we propose a set of algorithms that combine the anisotropic smoothing using the heat kernel with the outlier rejection capability of robust statistics. The proposed algorithms are applied on structural vector flows that model the internal shape variation in volumetric images. The 3D shapes are represented by sparse cross-sections along the main axis of the object. The dual directional block matching algorithm is used to initially extract the structural flows. This algorithm uses block matching between pixel blocks from consecutive images representing sparse cross-sections through a volume. Two flows are produced using forward and reverse matching along the main axis of the 3D object. After smoothing, the structural flows are used for slice interpolation. Experimental results provide a comparison among the given algorithms when used for digital 3D reconstruction of an incisor and of two human bones.

Original language	English
Title of host publication	2006 IEEE International Conference on Image Processing, ICIP 2006, Proceedings
Place of Publication	NEW YORK
Publisher	IEEE
Pages	1225-1228
Number of pages	4
ISBN (Print)	978-1-4244-0481-0
Publication status	Published - 2006
Event	IEEE International Conference on Image Processing (ICIP 2006) - Atlanta Duration: 8 Oct 2006 → 11 Oct 2006

Conference

Conference	IEEE International Conference on Image Processing (ICIP 2006)
City	Atlanta
Period	8/10/06 → 11/10/06

Keywords

median filters
diffusion equations
interpolation
biomedical imaging
OPTICAL-FLOW
ANISOTROPIC DIFFUSION
RECONSTRUCTION

Cite this

@inproceedings{d3c6de9d3863493f894860c1960f8e9f,

title = "Robust diffusion of structural flows for volumetric image interpolation",

abstract = "In this paper we propose a set of algorithms that combine the anisotropic smoothing using the heat kernel with the outlier rejection capability of robust statistics. The proposed algorithms are applied on structural vector flows that model the internal shape variation in volumetric images. The 3D shapes are represented by sparse cross-sections along the main axis of the object. The dual directional block matching algorithm is used to initially extract the structural flows. This algorithm uses block matching between pixel blocks from consecutive images representing sparse cross-sections through a volume. Two flows are produced using forward and reverse matching along the main axis of the 3D object. After smoothing, the structural flows are used for slice interpolation. Experimental results provide a comparison among the given algorithms when used for digital 3D reconstruction of an incisor and of two human bones.",

keywords = "median filters, diffusion equations, interpolation, biomedical imaging, OPTICAL-FLOW, ANISOTROPIC DIFFUSION, RECONSTRUCTION",

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

year = "2006",

language = "English",

isbn = "978-1-4244-0481-0",

pages = "1225--1228",

booktitle = "2006 IEEE International Conference on Image Processing, ICIP 2006, Proceedings",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Image Processing (ICIP 2006) ; Conference date: 08-10-2006 Through 11-10-2006",

}

TY - GEN

T1 - Robust diffusion of structural flows for volumetric image interpolation

AU - Doshi, Ashish

AU - Bors, Adrian G.

PY - 2006

Y1 - 2006

N2 - In this paper we propose a set of algorithms that combine the anisotropic smoothing using the heat kernel with the outlier rejection capability of robust statistics. The proposed algorithms are applied on structural vector flows that model the internal shape variation in volumetric images. The 3D shapes are represented by sparse cross-sections along the main axis of the object. The dual directional block matching algorithm is used to initially extract the structural flows. This algorithm uses block matching between pixel blocks from consecutive images representing sparse cross-sections through a volume. Two flows are produced using forward and reverse matching along the main axis of the 3D object. After smoothing, the structural flows are used for slice interpolation. Experimental results provide a comparison among the given algorithms when used for digital 3D reconstruction of an incisor and of two human bones.

AB - In this paper we propose a set of algorithms that combine the anisotropic smoothing using the heat kernel with the outlier rejection capability of robust statistics. The proposed algorithms are applied on structural vector flows that model the internal shape variation in volumetric images. The 3D shapes are represented by sparse cross-sections along the main axis of the object. The dual directional block matching algorithm is used to initially extract the structural flows. This algorithm uses block matching between pixel blocks from consecutive images representing sparse cross-sections through a volume. Two flows are produced using forward and reverse matching along the main axis of the 3D object. After smoothing, the structural flows are used for slice interpolation. Experimental results provide a comparison among the given algorithms when used for digital 3D reconstruction of an incisor and of two human bones.

KW - median filters

KW - diffusion equations

KW - interpolation

KW - biomedical imaging

KW - OPTICAL-FLOW

KW - ANISOTROPIC DIFFUSION

KW - RECONSTRUCTION

M3 - Conference contribution

SN - 978-1-4244-0481-0

SP - 1225

EP - 1228

BT - 2006 IEEE International Conference on Image Processing, ICIP 2006, Proceedings

PB - IEEE

CY - NEW YORK

T2 - IEEE International Conference on Image Processing (ICIP 2006)

Y2 - 8 October 2006 through 11 October 2006

ER -