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논문 기본 정보

자료유형
학술대회자료
저자정보
Rattikorn Sombutkaew (King Mongkut’s Institute of Technology Ladkrabang) Yothin Kumsang (Mahidol University) Orachat Chitsobuk (King Mongkut’s Institute of Technology Ladkrabang)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2014
발행연도
2014.10
수록면
521 - 524 (4page)

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초록· 키워드

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With the massive increment of patients’ medical information and images also limitation in transmission bandwidth, it is a challenging task for developing efficient medical information and image encoding techniques for digital picture archiving and communications (PACS). In order to achieve higher encoding efficiency, this research proposes adaptive quantization via fuzzy classified priority mapping. Image statistical characteristics are used as key features for Fuzzy C-mean clustering. The derived priority map is used to identify levels of importance for each image area. The significant candidates of irregular liver tissues, which need special doctor’s attention, will be assigned with higher priority than those from the regular ones. The higher the priority, the greater the number of bits assigned for encoding. An analysis of suitable quantization step size has been conducted. With the selection of appropriate quantization parameters for each priority level, the blocking artifacts can be greatly reduced. This results in quality improvement of the reconstructed images while the compression ratio remains reasonably high.

목차

Abstract
1. INTRODUCTION
2. THE PROPOSED METHOD
3. RESULTS
4. CONCLUSION
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