Medical Image Retrieval: Past and Present

Hwang, Kyung Hoon; Lee, Haejun; Choi, Duck-Joo

doi:10.4258/hir.2012.18.1.3

Cited by 69 publications

(31 citation statements)

References 26 publications

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“…Radiology content-based image retrieval (CBIR) is a key enabler for the utilization of previously acquired imaging data to assist radiologists in the decision-making process [11,24,31]. A CBIR system is an image search engine that retrieves medical records of patients with similar images from large archives.…”

Section: Introductionmentioning

confidence: 99%

Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scans

Spanier

Joskowicz

2017

Cloud-Based Benchmarking of Medical Image Analysis

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Automatic segmentation of anatomical structures in CT scans is an essential step in the analysis of radiological patient data and is a prerequisite for largescale content-based image retrieval (CBIR). Many existing segmentation methods are tailored to a single structure and/or require an atlas, which entails multistructure deformable registration and is time-consuming. We present a fully automatic atlasfree segmentation of multiple organs of the ventral cavity in contrast-enhanced CT scans of the whole trunk (CECT). Our method uses a pipeline approach based on the rules that determine the order in which the organs are isolated and how they are segmented. Each organ is individually segmented with a generic four-step procedure. Our method is unique in that it does not require any predefined atlas or a costly registration step and in that it uses the same generic segmentation approach for all organs. Experimental results on the segmentation of seven organs-liver, left and right kidneys, left and right lungs, trachea, and spleen-on 20 CECT scans of the VISCERAL Anatomy training dataset and 10 CECT scans of the test dataset yield an average DICE volume overlap similarity score of 90.95 and 88.50%, respectively. Source code is available at:

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Section: Introductionmentioning

confidence: 99%

Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scans

Spanier

Joskowicz

2017

Cloud-Based Benchmarking of Medical Image Analysis

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“…Content Based Medical Image Retrieval (CBMIR) (Ghosh et al, 2011;Kyung et al, 2012) is receiving a vigorous research to automate medical image database. CBMIR systems have increased attractiveness because of their neutral means of considering medical image content such as texture, shape, color.…”

Section: Introductionmentioning

confidence: 99%

Feature Dimension Reduction for Efficient Medical Image Retrieval System Using Unified Framework

Jaganathan¹

2013

Journal of Computer Science

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Feature dimensionality reduction problem is a major issue in Content Based Medical Image Retrieval (CBMIR) for the effective management of medical images with the support of visual features for the purpose of diagnosis and educational research field. The proposed CBMIR is used a unified approach based on extraction of visual features, optimized feature selection, classification of optimized features and similarity measurements. The Texture features are selected using Gray Level Co-occurrence Matrix (GLCM), Tamura Features (TF) and Gabor Filter (GF) in which pull out of features are formed a feature vector database. Fuzzy based PSO (FPSO) is applied for Feature selection to overcome the difficulty of feature vectors being surrounded in local optima of original PSO. This procedure also integrates a smart policymaking structure of ACO procedure into the novel FPSO where the global optimum position to be exclusive for every feature particle. The Fuzzy based Particle Swarm Optimization and Ant Colony Optimization (FPSO-ACO) technique is used to trim down the feature vector dimensionality and classification is accomplished using an extensive Fuzzy based Relevance Vector Machine (FRVM) to form collections of relevant image features that would provide an accepted way to classify dimensionally concentrated feature vectors of images. The Euclidean Distance (ED) is recognized as finest for similarity measurement between the medical query image and the medical image database. This proposed approach can acquire the query from the user and had retrieved the desired images from the database. The retrieval performance would be assessed based on precision and recall. This proposed CBMIR is used to provide comfort to the physician to obtain more assurance in their decisions for diagnosis and research students of medicine are keenness to get the crucial images fruitfully for additional investigation of their exploration.

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“…When this data is related to imaging technologies, it is referred to as a content-based image retrieval system. There are recent surveys on both class of applications [1,3,6,9,10]. In this work, however, we focused on the implementation of web-based applications, independently of whether the goal was as a medical decision tool or a CBIR.…”

Section: Web-based Applicationsmentioning

confidence: 99%

“…x x x x x n.d Rajala [48] CRDAS MRI x x n.d CRDAS Bond [49] ECG MRI HL7 x x x x x n.d Neubauer [50] SQL-Server n.d x x n.d HSM Haas [51] x own DB n.d x x n.d x EHR Baltasar [52] own DB X-Rays [10] own DB CT, X-Rays [17] n.d CT, X-Rays eXistdb x EHR Sethi [63] x n.d n.d. …”

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confidence: 99%

On the Use of XML in Medical Imaging Web-Based Applications

Mata

Oliver

Lalande

et al. 2017

IRBM

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The rapid growth of digital technology in medical fields over recent years has increased the need for applications able to manage patient medical records, imaging data, and chart information. Web-based applications are implemented with the purpose to link digital databases, storage and transmission protocols, management of large volumes of data and security concepts, allowing the possibility to read, analyze, and even diagnose remotely from the medical center where the information was acquired. The objective of this paper is to analyze the use of the XML protocol in web-based medical imaging applications, analyzing how this protocol allows indexing and exchanging the huge amount of information associated with each medical case. The purpose of this paper is to point out the main advantages and drawbacks of the XML technology in order to provide key ideas for future web-based applications. As already explained by the email of Dr. Alain Lalande, in this paper we review the advances that the XML exchanging information protocol has provided to web-based applications applied to the medical imaging field.As suggested, we've checked the associated editors list and we think that either Alfredo Hernandez or Frederique Frouin could manage the current submission.All authors have checked the manuscript and have agreed to the submission. We have no conflict of interest. We think the research topic the paper is dealing with perfectly fits the scope of the journal. Acknowledgements:This work was partially funded by the Spanish R+D+I grant n. TIN2012-37171-C02-01. C. Mata holds a Mediterranean Office for Youth mobility grant. Finally, the Regional Council of Burgundy under the PARI 1 scheme sponsored this work. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 On the use of XML in medical imaging web-based applications Title/Authors/Affiliations AbstractThe rapid growth of digital technology in medical fields over recent years has increased the need for applications able to manage patient medical records, imaging data, and chart information. Web-based applications are implemented with the purpose to link digital databases, storage and transmission protocols, management of large volumes of data and security concepts, allowing the possibility to read, analyze, and even diagnose remotely from the medical center where the information was acquired. The objective of this paper is to analyze the use of the XML protocol in webbased medical imaging applications, analyzing how this protocol allows indexing and exchanging the huge amount of information associated with each medical case. The purpose of this paper is to point out the main advantages and drawbacks of the XML technology in order to provide key ideas for future web-based applications.

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Medical Image Retrieval: Past and Present

Cited by 69 publications

References 26 publications

Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scans

Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scans

Feature Dimension Reduction for Efficient Medical Image Retrieval System Using Unified Framework

On the Use of XML in Medical Imaging Web-Based Applications

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