A new database for medical images and information

Tahmoush, Dave; Samet, Hanan

doi:10.1117/12.708309

Cited by 5 publications

(6 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Authors argued that this capability allowed a more efficient exchange of templates and would represent a step toward standardization. In a similar way, Tahmoush et al [36] also affirmed that the incorporation of DICOM 3 capability was necessary in medical image systems and that XML support should also be included. Indeed, it has become the preferred method for uploading data that was not already in DICOM format.…”

Section: Exchange Of Informationmentioning

confidence: 94%

“…The initial reluctance to PACS has vanished nowadays [58]. Different web-application have described the implementation of a PACS system in their work for the storage, research, transmission, evaluation of medical images [13] and even applied to telemedicine applications [36]. Jorritsma et al [55] studied the differences in usability terms of PACS with identical functionality, concluding that functional requirements alone are insufficient to determine the overall quality of a PACS.…”

Section: Databasesmentioning

confidence: 99%

See 1 more Smart Citation

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

Mata

Oliver

Lalande

et al. 2017

IRBM

View full text Add to dashboard Cite

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.

show abstract

Section: Exchange Of Informationmentioning

confidence: 94%

Section: Databasesmentioning

confidence: 99%

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

Mata

Oliver

Lalande

et al. 2017

IRBM

View full text Add to dashboard Cite

show abstract

“…Medical image databases have also used image similarity, from rule-based systems for chest radiographs [26] to anatomical structure matching [16,30,31,33] to learning techniques [14]. However, the focus is often on the non-cancerous structures, while it is the cancerous structures that are of principle interest.…”

Section: Introductionmentioning

confidence: 99%

“…The importance of similarity search grows in application areas such as multimedia, medical imaging, molecular biology, computer aided engineering, marketing and purchasing assistance, etc. [1,2,5,9,10,12,20,29,30,31,33]. To achieve effective retrieval, an image system must be able to accurately characterize and quantify perceptual similarity.…”

Section: Introductionmentioning

confidence: 99%

A learned distance function for medical image similarity retrieval

Tahmoush

2009

Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications

Self Cite

View full text Add to dashboard Cite

One fundamental problem remains in the area of image analysis and retrieval: how to measure perceptual similarity between two images. Most researchers employ a Minkowski-type metric, which does not reliably find similarities in objects that are obviously alike. This paper develops a similarity function that is learned in order to capture the perception of similarity. The technique first extracts high-level landmarks in the images to determine a local contextual similarity, but these are unordered and unregistered. Second, the point sets of the two images are fed into the learned similarity function to determine the overall similarity. This technique avoids arbitrary spatial constraints and is robust in the presence of noise, outliers, and imaging artifacts.

show abstract

“…The server can run on any machine using a Unix, Linux, or Windows operating system that can support Java 1.5 and MySQL. Additional details on the design can be found in [15].…”

Section: Designmentioning

confidence: 99%

A web collaboration system for content-based image retrieval of medical images

Tahmoush

Samet

2007

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

Building effective content-based image retrieval (CBIR) systems involves the combination of image creation, storage, security, transmission, analysis, evaluation feature extraction, and feature combination in order to store and retrieve medical images effectively. This requires the involvement of a large community of experts across several fields. We have created a CBIR system called Archimedes which integrates the community together without requiring disclosure of sensitive details.Archimedes' system design enables researchers to upload their feature sets and quickly compare the effectiveness of their methods against other stored feature sets. Additionally, research into the techniques used by radiologists is possible in Archimedes through doubleblind radiologist comparisons based on their annotations and feature markups.This research archive contains the essential technologies of secure transmission and storage, textual and feature searches, spatial searches, annotation searching, filtering of result sets, feature creation, and bulk loading of features, while creating a repository and testbed for the community.

show abstract

A new database for medical images and information

Cited by 5 publications

References 10 publications

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

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

A learned distance function for medical image similarity retrieval

A web collaboration system for content-based image retrieval of medical images

Contact Info

Product

Resources

About