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Evolution of Big Data in Medical Imaging Modalities to Extract Features Using Region Growing Segmentation, GLCM, and Discrete Wavelet Transform
- Publication Year :
- 2021
- Publisher :
- IGI Global, 2021.
-
Abstract
- Big data refers to the massive amount of data from sundry sources (gregarious media, healthcare, different sensor, etc.) with very high velocity. Due to expeditious growth, the multimedia or image data has rapidly incremented due to the expansion of convivial networking, surveillance cameras, satellite images, and medical images. Healthcare is the most promising area where big data can be applied to make a vicissitude in human life. The process for analyzing the intricate data is mundanely concerned with the disclosing of hidden patterns. In healthcare fields capturing the visual context of any medical images, extraction is a well introduced word in digital image processing. The motive of this research is to present a detailed overview of big data in healthcare and processing of non-invasive medical images with the avail of feature extraction techniques such as region growing segmentation, GLCM, and discrete wavelet transform.
- Subjects :
- Discrete wavelet transform
Modalities
Computer science
business.industry
Big data
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
020206 networking & telecommunications
Pattern recognition
02 engineering and technology
0202 electrical engineering, electronic engineering, information engineering
Medical imaging
020201 artificial intelligence & image processing
Artificial intelligence
Region growing segmentation
business
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....1fcf95471c2b9d1d72a490538d1c5540
- Full Text :
- https://doi.org/10.4018/978-1-7998-2795-5.ch003