English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In medical field the volume of medical image data produced every day is ever growing, particularly in grouping with the improved scanning resolutions and the importance of volumetric medical image data sets. In this work, five image compression methods are simulated. They are Karhunen-Loève Transform (KLT), Walsh-Hadamard Transform (WHT), Fast Fourier Transform (FFT), proposed Sparse Fast Fourier Transform (SFFT) and Discrete Cosine Transform (DCT). The results of simulation are shown and compared different quality parameters of it are by applying on various lung cancer CT Scan medical images. The DCT method algorithm was given better results like Compression Ratio (CR), Structural Content (SC), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) compare to other Transform methods. The DCT technique given improved result compared with other methods in all evaluation measures.

A Novel Approach on Discrete Cosion Transform Based Image Compression Technique For Lung Cancer