DOAJ Open Access 2022

A novel method of data compression using ROI for biomedical 2D images

Dankan Gowda V Avinash Sharma Rajesh L Mirzanur Rahman Ghazaala Yasmin +2 lainnya

Abstrak

In the era of modern medical imaging communal, huge volume of medical image data are being acquired and need to be transmitted and archived which necessitate the development of efficient image compression techniques on both 2D and 3D images. The compression of medical images is an essential process to support remote healthcare services. The medical diagnostics through these services require more accurate information from an image. As the property of inverse proportionality between the compression rate and quality of the image takes place in any kind of compression method, there is a need to sacrifice any one of those credentials (Quality or Compression Rate). With this context, Region of Interest (ROI) codecs are emerging and reduces this proportionality that yields more compression rate without compromising the quality. In this paper, presents an ROI based near lossless image compression method that incorporates the Set Partitioning in Hierarchical Trees (SPIHT) and Vector Quantization coding for medical images.

Topik & Kata Kunci

Electric apparatus and materials. Electric circuits. Electric networks

Penulis (7)

Dankan Gowda V

Avinash Sharma

Rajesh L

Mirzanur Rahman

Ghazaala Yasmin

Parismita Sarma

A. Azhagu Jaisudhan Pazhani

Format Sitasi

APA MLA BibTeX

V, D.G., Sharma, A., L, R., Rahman, M., Yasmin, G., Sarma, P. et al. (2022). A novel method of data compression using ROI for biomedical 2D images. https://doi.org/10.1016/j.measen.2022.100439

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Informasi Jurnal

Tahun Terbit: 2022
Sumber Database: DOAJ
DOI: 10.1016/j.measen.2022.100439
Akses: Open Access ✓