Literature DB >> 21975083

Generic integration of content-based image retrieval in computer-aided diagnosis.

Petra Welter1, Benedikt Fischer, Rolf W Günther, Thomas M Deserno né Lehmann.   

Abstract

Content-based image retrieval (CBIR) offers approved benefits for computer-aided diagnosis (CAD), but is still not well established in radiological routine yet. An essential factor is the integration gap between CBIR systems and clinical information systems. The international initiative Integrating the Healthcare Enterprise (IHE) aims at improving interoperability of medical computer systems. We took into account deficiencies in IHE compliance of current picture archiving and communication systems (PACS), and developed an intermediate integration scheme based on the IHE post-processing workflow integration profile (PWF) adapted to CBIR in CAD. The Image Retrieval in Medical Applications (IRMA) framework was used to apply our integration scheme exemplarily, resulting in the application called IRMAcon. The novel IRMAcon scheme provides a generic, convenient and reliable integration of CBIR systems into clinical systems and workflows. Based on the IHE PWF and designed to grow at a pace with the IHE compliance of the particular PACS, it provides sustainability and fosters CBIR in CAD.
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 21975083     DOI: 10.1016/j.cmpb.2011.08.010

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  A disease category feature database construction method of brain image based on deep convolutional neural network.

Authors:  Yanli Wan; Xifu Wang; Quan Chen; Xingyun Lei; Yan Wang; Chongde Chen; Hongpu Hu
Journal:  PLoS One       Date:  2020-06-01       Impact factor: 3.240

2.  Progressive privacy-preserving batch retrieval of lung CT image sequences based on edge-cloud collaborative computation.

Authors:  Yi Zhuang; Nan Jiang
Journal:  PLoS One       Date:  2022-09-15       Impact factor: 3.752

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.