Analytical Study of Medical PET Images by DWT and PCA

Authors

  • L-Fatma Hassan Al-Rubbiay
  • A.P.Dr. Husam Abulrazzak Rasheed

DOI:

https://doi.org/10.31272/jae.i141.1019

Keywords:

PET Medical Image , DIscrete of Wavelet TRansform ((DWT)) , Principal COmponent analysis((PCA)) , .

Abstract

The PET medical images need clarification to reach a correct diagnosis of the disease by removing noise from them, and this is done by applying several techniques, including DWT, PCA.  DWT is an algorithm that compresses an image and removes noise by dividing the image into several levels, removing the unnecessary (neglected) part of the image. The PCA algorithm compresses the error parameters in the image and then reconstructs them.

References

Roopali D. P., Sinivas H., Basavarj H.,2015, Medical Color Image Enhancement using Wavelet Transform and Contrast Stretching Technique, International Journal of scientific and Research Publications, ISSN 2250-3153.

Jianan C., Kuang G.,2019, PET image using unsupervised deep learning, European Journal of Nuclear and Medicine imaging, European Journal of Nuclear Medicine and Molecular Imaging.

Zahra F., Nidhal K. E., 2019, Detection and recognition of brain tumor based on DWT, PCA and ANN, Indonesian Journal of Electrical Engineering and Computer Science.

Vishnu N. S. ,Pooja S., The wavelet Transform An Introduction, Book 2014.

Toufik B., Mokhtar N., 2012, The Wavelet Transform for Image Processing Applications: Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology.

Ashwani K., Yadav, R.,2015, De-noising of Ultrasound Image using Discrete Wavelet Transform by Symlet Wavelet and Filters, International conference on Advances in Computing, Communications and Informatics .

Amal H. A., Abbas A., Jamila H., 2018, Image Compression Using Principal Component Analysis, Al-Mustansiriyah Journal of Science.

Kwang I. K., Matthias O. F., Bernhard S., 2010, Image Modeling based on Kernel Principle Component Analysis.

Published

2024-05-19