Intelligent shape feature extraction and indexing for efficient content-based medical image retrieval

Phillip A. Mlsna, Nikolay M. Sirakov

Research output: Contribution to conferencePaper

13 Scopus citations

Abstract

We describe the development of novel and efficient approaches and algorithms for a medical image content-based retrieval system capable of extracting and indexing key information about region shape. First, the general structure and the main components of the system are discussed. For grayscale segmentation to locate regions, we have explored a fast active contour approach based on the geometric heat differential equation. Region representation involves a set of extracted shape-based features. A technique for feature organization using N-dimensional feature vectors is employed. The image retrieval process compares similarity of query vectors to the indexed feature vectors. A convex hull model using the heat differential equation is used to organize the index of features to reduce the search space. Some experiments have been performed to test and validate certain portions of our approach. Finally, advantages and disadvantages together with the computational complexity of this system are discussed.

Original languageEnglish (US)
Pages172-176
Number of pages5
StatePublished - Jun 22 2004
Event2004 IEEE Southwest Symposium on Image Analysis and Interpretation - Lake Tahoe, NV, United States
Duration: Mar 28 2004Mar 30 2004

Other

Other2004 IEEE Southwest Symposium on Image Analysis and Interpretation
CountryUnited States
CityLake Tahoe, NV
Period3/28/043/30/04

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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    Mlsna, P. A., & Sirakov, N. M. (2004). Intelligent shape feature extraction and indexing for efficient content-based medical image retrieval. 172-176. Paper presented at 2004 IEEE Southwest Symposium on Image Analysis and Interpretation, Lake Tahoe, NV, United States.