DocumentCode
2575106
Title
Mega voltage X-ray image segmentation and ambient noise removal
Author
Iftekharuddin, K.M. ; Prajna, M. ; Samanth, S. ; Indhukuri, M.
Author_Institution
Memphis Univ., TN, USA
Volume
2
fYear
2002
fDate
2002
Firstpage
1111
Abstract
Mega voltage X-ray images are often characterized by low contrast, low resolution and image blurring. We explore efficient image segmentation of different types of mega voltage X-ray images using a specific neural processing technique called pulse coupled neural network (PCNN). We also study the usefulness of PCNN in ambient noise removal for the high voltage X-ray images.
Keywords
diagnostic radiography; feature extraction; image denoising; image resolution; image segmentation; medical image processing; neural nets; ambient noise removal; efficient image segmentation; feature extraction; high voltage X-ray images; image blurring; low contrast; low resolution; mega voltage X-ray image segmentation; specific neural processing technique; Biomedical applications of radiation; Hospitals; Image resolution; Image segmentation; Joining processes; Neural networks; Neurons; Pixel; Voltage; X-ray imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint
ISSN
1094-687X
Print_ISBN
0-7803-7612-9
Type
conf
DOI
10.1109/IEMBS.2002.1106302
Filename
1106302
Link To Document