Literature DB >> 7799686

I2C: a system for the indexing, storage, and retrieval of medical images by content.

S C Orphanoudakis1, C Chronaki, S Kostomanolakis.   

Abstract

Image indexing, storage, and retrieval based on pictorial content is a feature of image database systems which is becoming of increasing importance in many application domains. Medical image database systems, which support the retrieval of images generated by different modalities based on their pictorial content, will provide added value to future generation picture archiving and communication systems (PACS), and can be used as a diagnostic decision support tools and as a tool for medical research and training. We present the architecture and features of I2C, a system for the indexing, storage, and retrieval of medical images by content. A unique design feature of this architecture is that it also serves as a platform for the implementation and performance evaluation of image description methods and retrieval strategies. I2C is a modular and extensible system, which has been developed based on object-oriented principles. It consists of a set of cooperating modules which facilitate the addition of new graphical tools, image description and matching algorithms. These can be incorporated into the system at the application level. The core concept of I2C is an image class hierarchy. Image classes encapsulate different segmentation and image content description algorithms. Medical images are assigned to image classes based on a set of user-defined attributes such as imaging modality, type of study, anatomical characteristics, etc. This class-based treatment of images in the I2C system achieves increased accuracy and efficiency of content-based retrievals, by limiting the search space and allowing specific algorithms to be fine-tuned for images acquired by different modalities or representing different parts of the anatomy.

Mesh:

Year:  1994        PMID: 7799686     DOI: 10.3109/14639239409001378

Source DB:  PubMed          Journal:  Med Inform (Lond)        ISSN: 0307-7640


  9 in total

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3.  The application of the unified modeling language in object-oriented analysis of healthcare information systems.

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7.  Medical image retrieval: past and present.

Authors:  Kyung Hoon Hwang; Haejun Lee; Duckjoo Choi
Journal:  Healthc Inform Res       Date:  2012-03-31

8.  Modification of the mean-square error principle to double the convergence speed of a special case of Hopfield neural network used to segment pathological liver color images.

Authors:  Rachid Sammouda; Mohamed Sammouda
Journal:  BMC Med Inform Decis Mak       Date:  2004-12-12       Impact factor: 2.796

9.  A semantic medical multimedia retrieval approach using ontology information hiding.

Authors:  Kehua Guo; Shigeng Zhang
Journal:  Comput Math Methods Med       Date:  2013-09-09       Impact factor: 2.238

  9 in total

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