MyMedR

Displaying publications 1 - 20 of 29 in total

Abstract:

Sort:

Wavelet-based compression of medical images: filter-bank selection and evaluation

Saffor A, bin Ramli AR, Ng KH

Australas Phys Eng Sci Med, 2003 Jun;26(2):39-44.
PMID: 12956184

Wavelet-based image coding algorithms (lossy and lossless) use a fixed perfect reconstruction filter-bank built into the algorithm for coding and decoding of images. However, no systematic study has been performed to evaluate the coding performance of wavelet filters on medical images. We evaluated the best types of filters suitable for medical images in providing low bit rate and low computational complexity. In this study a variety of wavelet filters are used to compress and decompress computed tomography (CT) brain and abdomen images. We applied two-dimensional wavelet decomposition, quantization and reconstruction using several families of filter banks to a set of CT images. Discreet Wavelet Transform (DWT), which provides efficient framework of multi-resolution frequency was used. Compression was accomplished by applying threshold values to the wavelet coefficients. The statistical indices such as mean square error (MSE), maximum absolute error (MAE) and peak signal-to-noise ratio (PSNR) were used to quantify the effect of wavelet compression of selected images. The code was written using the wavelet and image processing toolbox of the MATLAB (version 6.1). This results show that no specific wavelet filter performs uniformly better than others except for the case of Daubechies and bi-orthogonal filters which are the best among all. MAE values achieved by these filters were 5 x 10(-14) to 12 x 10(-14) for both CT brain and abdomen images at different decomposition levels. This indicated that using these filters a very small error (approximately 7 x 10(-14)) can be achieved between original and the filtered image. The PSNR values obtained were higher for the brain than the abdomen images. For both the lossy and lossless compression, the 'most appropriate' wavelet filter should be chosen adaptively depending on the statistical properties of the image being coded to achieve higher compression ratio.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext UltiMatch-NL: a Web service matchmaker based on multiple semantic filters

Mohebbi K, Ibrahim S, Zamani M, Khezrian M

PLoS One, 2014;9(8):e104735.
PMID: 25157872 DOI: 10.1371/journal.pone.0104735

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Towards dynamic remote data auditing in computational clouds

Sookhak M, Akhunzada A, Gani A, Khurram Khan M, Anuar NB

ScientificWorldJournal, 2014;2014:269357.
PMID: 25121114 DOI: 10.1155/2014/269357

Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Stochastic optimized relevance feedback particle swarm optimization for content based image retrieval

Imran M, Hashim R, Noor Elaiza AK, Irtaza A

ScientificWorldJournal, 2014;2014:752090.
PMID: 25121136 DOI: 10.1155/2014/752090

One of the major challenges for the CBIR is to bridge the gap between low level features and high level semantics according to the need of the user. To overcome this gap, relevance feedback (RF) coupled with support vector machine (SVM) has been applied successfully. However, when the feedback sample is small, the performance of the SVM based RF is often poor. To improve the performance of RF, this paper has proposed a new technique, namely, PSO-SVM-RF, which combines SVM based RF with particle swarm optimization (PSO). The aims of this proposed technique are to enhance the performance of SVM based RF and also to minimize the user interaction with the system by minimizing the RF number. The PSO-SVM-RF was tested on the coral photo gallery containing 10908 images. The results obtained from the experiments showed that the proposed PSO-SVM-RF achieved 100% accuracy in 8 feedback iterations for top 10 retrievals and 80% accuracy in 6 iterations for 100 top retrievals. This implies that with PSO-SVM-RF technique high accuracy rate is achieved at a small number of iterations.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics

Pahl C, Zare M, Nilashi M, de Faria Borges MA, Weingaertner D, Detschew V, et al.

J Biomed Inform, 2015 Jun;55:174-87.
PMID: 25900270 DOI: 10.1016/j.jbi.2015.04.004

This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works.

Matched MeSH terms: Information Storage and Retrieval/methods*
ProLysED: an integrated database and meta-server of bacterial protease systems

Firdaus Raih M, Ahmad HA, Sharum MY, Azizi N, Mohamed R

Appl. Bioinformatics, 2005;4(2):147-50.
PMID: 16128617

Bacterial proteases are an important group of enzymes that have very diverse biochemical and cellular functions. Proteases from prokaryotic sources also have a wide range of uses, either in medicine as pathogenic factors or in industry and therapeutics. ProLysED (Prokaryotic Lysis Enzymes Database), our meta-server integrated database of bacterial proteases, is a useful, albeit very niche, resource. The features include protease classification browsing and searching, organism-specific protease browsing, molecular information and visualisation of protease structures from the Protein Data Bank (PDB) as well as predicted protease structures.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Multistrategy self-organizing map learning for classification problems

Hasan S, Shamsuddin SM

Comput Intell Neurosci, 2011;2011:121787.
PMID: 21876686 DOI: 10.1155/2011/121787

Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test.

Matched MeSH terms: Information Storage and Retrieval/methods
Multiresolution wavelet analysis for efficient analysis, compression and remote display of long-term physiological signals

Khuan LY, Bister M, Blanchfield P, Salleh YM, Ali RA, Chan TH

Australas Phys Eng Sci Med, 2006 Jun;29(2):216-28.
PMID: 16845928

Increased inter-equipment connectivity coupled with advances in Web technology allows ever escalating amounts of physiological data to be produced, far too much to be displayed adequately on a single computer screen. The consequence is that large quantities of insignificant data will be transmitted and reviewed. This carries an increased risk of overlooking vitally important transients. This paper describes a technique to provide an integrated solution based on a single algorithm for the efficient analysis, compression and remote display of long-term physiological signals with infrequent short duration, yet vital events, to effect a reduction in data transmission and display cluttering and to facilitate reliable data interpretation. The algorithm analyses data at the server end and flags significant events. It produces a compressed version of the signal at a lower resolution that can be satisfactorily viewed in a single screen width. This reduced set of data is initially transmitted together with a set of 'flags' indicating where significant events occur. Subsequent transmissions need only involve transmission of flagged data segments of interest at the required resolution. Efficient processing and code protection with decomposition alone is novel. The fixed transmission length method ensures clutter-less display, irrespective of the data length. The flagging of annotated events in arterial oxygen saturation, electroencephalogram and electrocardiogram illustrates the generic property of the algorithm. Data reduction of 87% to 99% and improved displays are demonstrated.

Matched MeSH terms: Information Storage and Retrieval/methods*
Leveraging intelligent agents for knowledge discovery from heterogeneous healthcare data repositories

Zaidi SZ, Abidi SS, Manickam S

Stud Health Technol Inform, 2002;90:335-40.
PMID: 15460713

This paper presents a case for an intelligent agent based framework for knowledge discovery in a distributed healthcare environment comprising multiple heterogeneous healthcare data repositories. Data-mediated knowledge discovery, especially from multiple heterogeneous data resources, is a tedious process and imposes significant operational constraints on end-users. We demonstrate that autonomous, reactive and proactive intelligent agents provide an opportunity to generate end-user oriented, packaged, value-added decision-support/strategic planning services for healthcare professionals, manages and policy makers, without the need for a priori technical knowledge. Since effective healthcare is grounded in good communication, experience sharing, continuous learning and proactive actions, we use intelligent agents to implement an Agent based Data Mining Infostructure that provides a suite of healthcare-oriented decision-support/strategic planning services.

Matched MeSH terms: Information Storage and Retrieval/methods*
Glove-based approach to online signature verification

Kamel NS, Sayeed S, Ellis GA

IEEE Trans Pattern Anal Mach Intell, 2008 Jun;30(6):1109-13.
PMID: 18421114 DOI: 10.1109/TPAMI.2008.32

Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.

Matched MeSH terms: Information Storage and Retrieval/methods
Fulltext Getting to know journal bibliographic databases

Ng KH, Peh WC

Singapore Med J, 2010 Oct;51(10):757-60; quiz 761.
PMID: 21103809

A bibliographic database is an organised digital collection of references to published literature. A bibliographic database may be general in scope or may cover a specific academic discipline. There are many types of medical and general bibliographic databases. They cover biomedical and scientific literature, morbidity and mortality statistics, therapeutic regimens, medical records, images and reviews of evidence-based medicine. Getting to know these databases will help researchers and authors to enhance their writing and publishing endeavours.

Matched MeSH terms: Information Storage and Retrieval/methods*
Evaluation of medical image watermarking with tamper detection and recovery (AW-TDR)

Zain JM, Fauzi AR

Annu Int Conf IEEE Eng Med Biol Soc, 2007;2007:5662-5.
PMID: 18003297

This paper will study and evaluate watermarking technique by Zain and Fauzi [1]. Recommendations will then be made to enhance the technique especially in the aspect of recovery or reconstruction rate for medical images. A proposal will also be made for a better distribution of watermark to minimize the distortion of the Region of Interest (ROI). The final proposal will enhance AW-TDR in three aspects; firstly the image quality in the ROI will be improved as the maximum change is only 2 bits in every 4 pixels, or embedding rate of 0.5 bits/pixel. Secondly the recovery rate will also be better since the recovery bits are located outside the region of interest. The disadvantage in this is that, only manipulation done in the ROI will be detected. Thirdly the quality of the reconstructed image will be enhanced since the average of 2 x 2 pixels would be used to reconstruct the tampered image.

Matched MeSH terms: Information Storage and Retrieval/methods*
Evaluation of a content-based retrieval system for blood cell images with automated methods

Seng WC, Mirisaee SH

J Med Syst, 2011 Aug;35(4):571-8.
PMID: 20703533 DOI: 10.1007/s10916-009-9393-3

Content-based image retrieval techniques have been extensively studied for the past few years. With the growth of digital medical image databases, the demand for content-based analysis and retrieval tools has been increasing remarkably. Blood cell image is a key diagnostic tool for hematologists. An automated system that can retrieved relevant blood cell images correctly and efficiently would save the effort and time of hematologists. The purpose of this work is to develop such a content-based image retrieval system. Global color histogram and wavelet-based methods are used in the prototype. The system allows users to search by providing a query image and select one of four implemented methods. The obtained results demonstrate the proposed extended query refinement has the potential to capture a user's high level query and perception subjectivity by dynamically giving better query combinations. Color-based methods performed better than wavelet-based methods with regard to precision, recall rate and retrieval time. Shape and density of blood cells are suggested as measurements for future improvement. The system developed is useful for undergraduate education.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Effect of temporal relationships in associative rule mining for web log data

Khairudin NM, Mustapha A, Ahmad MH

ScientificWorldJournal, 2014;2014:813983.
PMID: 24587757 DOI: 10.1155/2014/813983

The advent of web-based applications and services has created such diverse and voluminous web log data stored in web servers, proxy servers, client machines, or organizational databases. This paper attempts to investigate the effect of temporal attribute in relational rule mining for web log data. We incorporated the characteristics of time in the rule mining process and analysed the effect of various temporal parameters. The rules generated from temporal relational rule mining are then compared against the rules generated from the classical rule mining approach such as the Apriori and FP-Growth algorithms. The results showed that by incorporating the temporal attribute via time, the number of rules generated is subsequently smaller but is comparable in terms of quality.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Development of a kidney TeleUltrasound consultation system

Hassan A, Ibrahim F

J Digit Imaging, 2011 Apr;24(2):308-13.
PMID: 20386951 DOI: 10.1007/s10278-010-9283-8

This paper presents the development of kidney TeleUltrasound consultation system. The TeleUltrasound system provides an innovative design that aids the acquisition, archiving, and dissemination of medical data and information over the internet as its backbone. The system provides data sharing to allow remote collaboration, viewing, consultation, and diagnosis of medical data. The design is layered upon a standard known as Digital Imaging and Communication in Medicine (DICOM). The DICOM standard defines protocols for exchanging medical images and their associated data. The TeleUltrasound system is an integrated solution for retrieving, processing, and archiving images and providing data storage management using Structured Query Language (SQL) database. Creating a web-based interface is an additional advantage to achieve global accessibility of experts that will widely open the opportunity of greater examination and multiple consultations. This system is equipped with a high level of data security and its performance has been tested with white, black, and gray box techniques. And the result was satisfactory. The overall system has been evaluated by several radiologists in Malaysia, United Arab Emirates, and Sudan, the result is shown within this paper.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Development of a Search Strategy for an Evidence Based Retrieval Service

Ho GJ, Liew SM, Ng CJ, Hisham Shunmugam R, Glasziou P

PLoS One, 2016;11(12):e0167170.
PMID: 27935993 DOI: 10.1371/journal.pone.0167170

BACKGROUND: Physicians are often encouraged to locate answers for their clinical queries via an evidence-based literature search approach. The methods used are often not clearly specified. Inappropriate search strategies, time constraint and contradictory information complicate evidence retrieval.
AIMS: Our study aimed to develop a search strategy to answer clinical queries among physicians in a primary care setting.
METHODS: Six clinical questions of different medical conditions seen in primary care were formulated. A series of experimental searches to answer each question was conducted on 3 commonly advocated medical databases. We compared search results from a PICO (patients, intervention, comparison, outcome) framework for questions using different combinations of PICO elements. We also compared outcomes from doing searches using text words, Medical Subject Headings (MeSH), or a combination of both. All searches were documented using screenshots and saved search strategies.
RESULTS: Answers to all 6 questions using the PICO framework were found. A higher number of systematic reviews were obtained using a 2 PICO element search compared to a 4 element search. A more optimal choice of search is a combination of both text words and MeSH terms. Despite searching using the Systematic Review filter, many non-systematic reviews or narrative reviews were found in PubMed. There was poor overlap between outcomes of searches using different databases. The duration of search and screening for the 6 questions ranged from 1 to 4 hours.
CONCLUSION: This strategy has been shown to be feasible and can provide evidence to doctors' clinical questions. It has the potential to be incorporated into an interventional study to determine the impact of an online evidence retrieval system.

Matched MeSH terms: Information Storage and Retrieval/methods*
Determination of skin repigmentation progression

Nugroho H, Fadzil MH, Yap VV, Norashikin S, Suraiya HH

Annu Int Conf IEEE Eng Med Biol Soc, 2007;2007:3442-5.
PMID: 18002737

In this paper, we describe an image processing scheme to analyze and determine areas of skin that have undergone repigmentation in particular, during the treatment of vitiligo. In vitiligo cases, areas of skin become pale or white due to the lack of skin pigment called melanin. Vitiligo treatment causes skin repigmentation resulting in a normal skin color. However, it is difficult to determine and quantify the amount of repigmentation visually during treatment because the repigmentation progress is slow and moreover changes in skin color can only be discerned over a longer time frame typically 6 months. Here, we develop a digital image analysis scheme that can identify and determine vitiligo skin areas and repigmentation progression on a shorter time period. The technique is based on principal component analysis and independent component analysis which converts the RGB skin image into a skin image that represent skin areas due to melanin and haemoglobin only, followed by segmentation process. Vitiligo skin lesions are identified as skin areas that lack melanin (non-melanin areas). In the initial studies of 4 patients, the method has been able to quantify repigmentation in vitiligo lesion. Hence it is now possible to determine repigmentation progression objectively and treatment efficacy on a shorter time cycle.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext Design and development of a content-based medical image retrieval system for spine vertebrae irregularity

Mustapha A, Hussain A, Samad SA, Zulkifley MA, Diyana Wan Zaki WM, Hamid HA

Biomed Eng Online, 2015;14:6.
PMID: 25595511 DOI: 10.1186/1475-925X-14-6

Content-based medical image retrieval (CBMIR) system enables medical practitioners to perform fast diagnosis through quantitative assessment of the visual information of various modalities.

Matched MeSH terms: Information Storage and Retrieval/methods*
Fulltext DAD-match; Security technique to prevent denial of service attack on duplicate address detection process in IPv6 link-local network

Al-Ani AK, Anbar M, Manickam S, Al-Ani A

PLoS One, 2019;14(4):e0214518.
PMID: 30939154 DOI: 10.1371/journal.pone.0214518

An efficiently unlimited address space is provided by Internet Protocol version 6 (IPv6). It aims to accommodate thousands of hundreds of unique devices on a similar link. This can be achieved through the Duplicate Address Detection (DAD) process. It is considered one of the core IPv6 network's functions. It is implemented to make sure that IP addresses do not conflict with each other on the same link. However, IPv6 design's functions are exposed to security threats like the DAD process, which is vulnerable to Denial of Service (DoS) attack. Such a threat prevents the host from configuring its IP address by responding to each Neighbor Solicitation (NS) through fake Neighbor Advertisement (NA). Various mechanisms have been proposed to secure the IPv6 DAD procedure. The proposed mechanisms, however, suffer from complexity, high processing time, and the consumption of more resources. The experiments-based findings revealed that all the existing mechanisms had failed to secure the IPv6 DAD process. Therefore, DAD-match security technique is proposed in this study to efficiently secure the DAD process consuming less processing time. DAD-match is built based on SHA-3 to hide the exchange tentative IP among hosts throughout the process of DAD in an IPv6 link-local network. The obtained experimental results demonstrated that the DAD-match security technique achieved less processing time compared with the existing mechanisms as it can resist a range of different threats like collision and brute-force attacks. The findings concluded that the DAD-match technique effectively prevents the DoS attack during the DAD process. The DAD-match technique is implemented on a small area IPv6 network; hence, the author future work is to implement and test the DAD-match technique on a large area IPv6 network.

Matched MeSH terms: Information Storage and Retrieval/methods
Fulltext Creation of reliable relevance judgments in information retrieval systems evaluation experimentation through crowdsourcing: a review

Samimi P, Ravana SD

ScientificWorldJournal, 2014;2014:135641.
PMID: 24977172 DOI: 10.1155/2014/135641

Test collection is used to evaluate the information retrieval systems in laboratory-based evaluation experimentation. In a classic setting, generating relevance judgments involves human assessors and is a costly and time consuming task. Researchers and practitioners are still being challenged in performing reliable and low-cost evaluation of retrieval systems. Crowdsourcing as a novel method of data acquisition is broadly used in many research fields. It has been proven that crowdsourcing is an inexpensive and quick solution as well as a reliable alternative for creating relevance judgments. One of the crowdsourcing applications in IR is to judge relevancy of query document pair. In order to have a successful crowdsourcing experiment, the relevance judgment tasks should be designed precisely to emphasize quality control. This paper is intended to explore different factors that have an influence on the accuracy of relevance judgments accomplished by workers and how to intensify the reliability of judgments in crowdsourcing experiment.

Matched MeSH terms: Information Storage and Retrieval/methods*

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links