Bridging the Abridged

Gao, Xiaohong; Loomes, Martin J.; Comley, Richard

doi:10.4018/978-1-4666-0888-7.ch017

“…They are of texture representations including 3D Grey Level Co-occurrence Matrices (3D GLCM), 3D Wavelet Transforms (3D WT), 3D Gabor Transforms (3D GT) and 3D Local Binary Pattern (3D LBP). The details of these 3D texture representations for 3D brain can be found in [23,24,25].…”

Section: Retrieval Resultsmentioning

confidence: 99%

“…By comparing the left half with its right counterpart of a hemisphere along this middle symmetry plane, the abnormality is envisaged to be singled out. The details of potential VOI selection by using Bhattacharya Coefficient and experimental results can be found in [23,24].…”

Section: Potential Voi Selectionmentioning

confidence: 99%

3D CBIR with sparse coding for image-guided neurosurgery

Yu

¹

,

Hui

²

,

Gao

³

2013

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an open access repository of Middlesex University research http://eprints.mdx.ac.uk Qian, Yu; Hui, Rui; Gao, Xiaohong W., 2012. 3D CBIR with sparse coding for image-guided neurosurgery. Available from Middlesex University's Research Repository. Copyright:Middlesex University Research Repository makes the University's research available electronically.Copyright and moral rights to this work are retained by the author and/or other copyright owners. No part of the work may be sold or exploited commercially in any format or medium without the prior written permission of the copyright holder(s). A copy may be downloaded for personal, noncommercial, research or study without prior permission and without charge. Any use of the work for private study or research must be properly acknowledged with reference to the work's full bibliographic details.This work may not be reproduced in any format or medium, or extensive quotations taken from it, or its content changed in any way, without first obtaining permission in writing from the copyright holder(s).If you believe that any material held in the repository infringes copyright law, please contact the Repository Team at Middlesex University via the following email address: eprints@mdx.ac.ukThe item will be removed from the repository while any claim is being investigated. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Abstract: This research takes an application-specific approach to investigate, extend and implement the state of the art in the fields of both visual information retrieval and machine learning, bridging the gap between theoretical models and real world applications. During an image-guided neurosurgery, path planning remains the foremost and hence the most important step to perform an operation and ensures the maximum resection of an intended target and minimum sacrifice of health tissues. In this investigation, the technique of content-based image retrieval (CBIR) coupled with machine learning algorithms are exploited in designing a computer aided path planning system (CAP) to assist junior doctors in planning surgical paths while sustaining the highest precision. Specifically, after evaluation of approaches of sparse coding and K-means in constructing a codebook, the model of sparse codes of 3D SIFT has been furthered and thereafter employed for retrieving, The novelty of this work lies in the fact that not only the existing algorithms for 2D images have been successfully extended into 3D space, leading to promising results, but also the application of CBIR, that is mainly in a research realm, to a clinical sector can be achieved by th...

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Telemedicine and Electronic Health

Kasemsap

¹

2017

Health Information Systems and the Advancement of Medical Practice in Developing Countries

6

0

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This chapter reveals the overview of telemedicine; telemedicine in developing countries; Electronic Health Record (EHR); and mobile health technologies. Telemedicine and Electronic Health (e-health) are modern technologies toward improving quality of care and increasing patient safety in developing countries. Telemedicine and e-health are the utilization of medical information exchanged from one site to another site via electronic communications. Telemedicine and e-health help health care organizations share data contained in the largely proprietary EHR systems in developing countries. Telemedicine and e-health help reduce the cost of health care and increases the efficiency through better management of chronic diseases, shared health professional staffing, reduced travel times, and shorter hospital stays. The chapter argues that utilizing telemedicine and e-health has the potential to enhance health care performance and reach strategic goals in developing countries.

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Telemedicine and Electronic Health

Kasemsap

¹

2018

Health Economics and Healthcare Reform

0

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This chapter reveals the overview of telemedicine; telemedicine in developing countries; Electronic Health Record (EHR); and mobile health technologies. Telemedicine and Electronic Health (e-health) are modern technologies toward improving quality of care and increasing patient safety in developing countries. Telemedicine and e-health are the utilization of medical information exchanged from one site to another site via electronic communications. Telemedicine and e-health help health care organizations share data contained in the largely proprietary EHR systems in developing countries. Telemedicine and e-health help reduce the cost of health care and increases the efficiency through better management of chronic diseases, shared health professional staffing, reduced travel times, and shorter hospital stays. The chapter argues that utilizing telemedicine and e-health has the potential to enhance health care performance and reach strategic goals in developing countries.

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Bridging the Abridged

Cited by 3 publications

References 22 publications

3D CBIR with sparse coding for image-guided neurosurgery

3D CBIR with sparse coding for image-guided neurosurgery

Telemedicine and Electronic Health

Telemedicine and Electronic Health

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