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Dive into the research topics where Kanchana Rathnayaka is active.

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Featured researches published by Kanchana Rathnayaka.


Medical Engineering & Physics | 2011

Effects of CT image segmentation methods on the accuracy of long bone 3D reconstructions

Kanchana Rathnayaka; Tony Sahama; Michael Schuetz; Beat Schmutz

An accurate and accessible image segmentation method is in high demand for generating 3D bone models from CT scan data, as such models are required in many areas of medical research. Even though numerous sophisticated segmentation methods have been published over the years, most of them are not readily available to the general research community. Therefore, this study aimed to quantify the accuracy of three popular image segmentation methods, two implementations of intensity thresholding and Canny edge detection, for generating 3D models of long bones. In order to reduce user dependent errors associated with visually selecting a threshold value, we present a new approach of selecting an appropriate threshold value based on the Canny filter. A mechanical contact scanner in conjunction with a microCT scanner was utilised to generate the reference models for validating the 3D bone models generated from CT data of five intact ovine hind limbs. When the overall accuracy of the bone model is considered, the three investigated segmentation methods generated comparable results with mean errors in the range of 0.18-0.24 mm. However, for the bone diaphysis, Canny edge detection and Canny filter based thresholding generated 3D models with a significantly higher accuracy compared to those generated through visually selected thresholds. This study demonstrates that 3D models with sub-voxel accuracy can be generated utilising relatively simple segmentation methods that are available to the general research community.


Biomedical spectroscopy and imaging | 2013

Anatomical MR imaging of long bones: Comparative performance of MRI at 1.5 T and 3 T

Kanchana Rathnayaka; Konstantin I. Momot; Alan Coulthard; Andrew Volp; Tony Sahama; Michael Schütz; Beat Schmutz

The current gold standard for the design of orthopaedic implants is 3D models of long bones obtained using computed tomography (CT). However, high-resolution CT imaging involves high radiation exposure, which limits its use in healthy human volunteers. Magnetic resonance imaging (MRI) is an attractive alternative for the scanning of healthy human volunteers for research purposes. Current limitations of MRI include difficulties of tissue segmentation within joints and long scanning times. In this work, we explore the possibility of overcoming these limitations through the use of MRI scanners operating at a higher field strength. We quantitatively compare the quality of anatomical MR images of long bones obtained at 1.5 T and 3 T and optimise the scanning protocol of 3 T MRI. FLASH images of the right leg of five human volunteers acquired at 1.5 T and 3 T were compared in terms of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The comparison showed a relatively high CNR and SNR at 3 T for most regions of the femur and tibia, with the exception of the distal diaphyseal region of the femur and the mid diaphyseal region of the tibia. This was accompanied by an ~65% increase in the longitudinal spin relaxation time (T1) of the muscle at 3 T compared to 1.5 T. The results suggest that MRI at 3 T may be able to enhance the segmentability and potentially improve the accuracy of 3D anatomical models of long bones, compared to 1.5 T. We discuss how the total imaging times at 3 T can be kept short while maximising the CNR and SNR of the images obtained.


Journal of Biomechanics | 2010

A new approach for assigning bone material properties from CT images into finite element models

Gongfa Chen; Beat Schmutz; Devakar Epari; Kanchana Rathnayaka; Salma Ibrahim; Michael Schuetz; Mark J. Pearcy


Injury-international Journal of The Care of The Injured | 2010

Quantitative fit assessment of tibial nail designs using 3D computer modelling

Beat Schmutz; Kanchana Rathnayaka; Martin E. Wullschleger; John Meek; Michael Schuetz


Institute of Health and Biomedical Innovation; Science & Engineering Faculty | 2013

Correction of step artefact associated with MRI scanning of long bones

Kanchana Rathnayaka; Gary Cowin; Michael Schuetz; Tony Sahama; Beat Schmutz


Orthopaedic Proceedings | 2012

QUANTITATIVE FIT ASSESSMENT OF TIBIAL NAIL DESIGNS USING 3D COMPUTER MODELLING

Beat Schmutz; Kanchana Rathnayaka; Martin E. Wullschleger; John Meek; Michael Schuetz


Institute of Health and Biomedical Innovation; Science & Engineering Faculty | 2012

Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models

Kanchana Rathnayaka; Konstantin I. Momot; Hansrudi Noser; Andrew Volp; Michael Schuetz; Tony Sahama; Beat Schmutz


Faculty of Built Environment and Engineering; Institute of Health and Biomedical Innovation | 2010

A new approach for assigning bone material properties from CT images into finite lement models

Gongfa Chen; Beat Schmutz; Devakara R. Epari; Kanchana Rathnayaka; Salma Ibrahim; Michael Schuetz; Mark J. Pearcy


Faculty of Built Environment and Engineering; Faculty of Science and Technology; Institute of Health and Biomedical Innovation | 2010

Improved image contrast of the bone-muscle interface with 3T MRI compared to 1.5T MRI [Abstract]

Kanchana Rathnayaka; Alan Coulthard; Konstantin I. Momot; Andrew Volp; Tony Sahama; Michael Schuetz; Beat Schmutz


Faculty of Built Environment and Engineering; Faculty of Science and Technology; Institute of Health and Biomedical Innovation | 2009

Quantification of the accuracy of MRI generated 3D models of long bones

Kanchana Rathnayaka; Konstantin I. Momot; Andrew Volp; Hansrudi Noser; Tony Sahama; Michael Schuetz; Beat Schmutz

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Beat Schmutz

Queensland University of Technology

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Michael Schuetz

Queensland University of Technology

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Tony Sahama

Queensland University of Technology

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Andrew Volp

Princess Alexandra Hospital

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Konstantin I. Momot

Queensland University of Technology

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Alan Coulthard

Royal Brisbane and Women's Hospital

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Gongfa Chen

Queensland University of Technology

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Mark J. Pearcy

Queensland University of Technology

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Martin E. Wullschleger

Queensland University of Technology

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Salma Ibrahim

Queensland University of Technology

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