Enhancement of texture feature Extraction for Content based retrieval of medical Images
Document Type
News Article
Abstract
The content of medical images is described by features. Features of each medical image are extracted and stored in the database. In order to carry out content-based medical image retrieval, these features are classified into statistical, structural, spectral and transform types. These classifications are based on the content of feature. It is often desirable or even critical to speed up the processing of such large image data sets. Complex image processing methods can be very time consuming and their computation can be challenging even for recent computer hardware. There is a need to exploit massive parallelism while processing of such large image data sets. There is a need to integrate the parallel languages to achieve the nature of massive parallelism while processing such images.
Weblink for the recent publications:
- https://manipal.pure.elsevier.com/en/publications/algorithms-for-extracting-various-local-texture-features
- https://manipal.pure.elsevier.com/en/publications/%CE%B81-time-complexity-parallel-local-binary-pattern-feature-extracto
- https://manipal.pure.elsevier.com/en/publications/parallelization-of-local-diagonal-extrema-pattern-using-a-graphic
Publication Date
Spring 10-30-2022
Recommended Citation
., N. Gopalakrishna Kini Dr, "Enhancement of texture feature Extraction for Content based retrieval of medical Images" (2022). Technical Collection. 47.
https://impressions.manipal.edu/technical-collection/47
