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Efficient medical image transformation method for lossless compression by considering real time applications

Sepehrband, F ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/ICSPCS.2010.5709763
  3. Publisher: 2010
  4. Abstract:
  5. Medical images contain human body pictures and used widely in diagnosis and surgical purposes [1]. Compression is needed for medical images for some applications such as profiling patient's data or transmission systems Due to the importance of the information of medical images, lossless or visually lossless compression preferred. Lossless compression mainly consists of transformation and encoding steps. On the other hand, hardware implementation of lossless compression algorithm accelerates real time tasks such as online diagnosis and telemedicine. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well known methods for lossless compression. This paper is focused on the transformation step of compression and introduced a new transformation which is efficient in both entropy reduction and computational complexity. A new method is then achieved by improving the perdition model which is used in lossless JPEG. Our new transformation increases the energy compaction of prediction model and as a result reduces entropy value of transformed image. However, our new method is low complex. After a mathematical proof for efficiency of the new method, it is applied to more than hundreds of test-cases and the results are compared with previous methods and it shows about 8 percent improvement in average. As a result, the new algorithm shows a better efficiency for transforming lossless medical images, especially for online applications
  6. Keywords:
  7. Image transformation ; Standards ; Energy compaction ; Entropy reduction ; Entropy value ; Hardware implementations ; Human bodies ; Image transformations ; JPEG ; JPEG 2000 ; JPEG-LS ; Lossless ; Lossless compression ; Lossless compression algorithm ; Mathematical proof ; Medical images ; On-line applications ; On-line diagnosis ; Prediction model ; Real-time application ; Real-time tasks ; Test case ; Transmission systems ; Algorithms ; Communication systems ; Compaction ; Computational complexity ; Data visualization ; Entropy ; Hardware ; Image compression ; Mathematical models ; Signal processing ; Medical imaging
  8. Source: 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings, 13 December 2010 through 15 December 2010, Gold Coast, QLD ; 2010 ; 9781424479078 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/5709763