한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제19권2호
  • /
  • Pages.133-142
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  • 2014
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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수정된 감마 코딩 기반 의료 검진 데이터 압축

Compression of Medical Examination Data Based on Modified Gamma-Coding

  • 구동윤 (동국대학교 컴퓨터공학과-서울) ;
  • 박재욱 (동국대학교 컴퓨터공학과-서울) ;
  • 이용규 (동국대학교 컴퓨터공학과-서울)
  • Ku, Dong Youn (Dept. of Computer Science & Engineering, Dongguk University-Seoul) ;
  • Park, Jae Wook (Dept. of Computer Science & Engineering, Dongguk University-Seoul) ;
  • Lee, Yong Kyu (Dept. of Computer Science & Engineering, Dongguk University-Seoul)
  • 투고 : 2013.06.18
  • 심사 : 2013.12.09
  • 발행 : 2014.02.28
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초록

의료 정보 시스템의 발달로 인해 환자들의 진료 시간이 짧아지고 그에 따라 진료 받는 환자들의 수가 증가하여 진료 데이터 양이 급속도로 증가하고 있으며, 증가하는 환자들의 데이터를 효율적으로 저장, 관리하기 위해 다양한 압축 방법에 대한 연구가 진행 중이다. 그러나 기존 방법들은 측정값을 원시 데이터로 압축하여 저장하기 때문에 압축률이 떨어지는 단점이 있다. 이러한 문제를 해결하기 위해 본 논문에서는 비트 단위로 압축 가능한 감마 코딩 기법을 이용하여 측정값과 정상범위 값과의 편차를 부호화하여 압축하는 방법을 제안한다. 또한 측정값과 편차가 가장 작은 과거 데이터를 기준치로 삼아 그 편차를 부호화하여 압축하는 방법을 제안한다. 제안하는 방법은 매우 간단하며 편차를 압축하기 때문에 기존 방법보다 압축률이 높은 장점이 있다. 성능평가를 통하여 제안한 방법이 기존 압축방법보다 우수하다는 것을 검증한다.

According to the development of medical information systems, shortened examination time per patient could increase the number of treatments, resulting in the rapid growth of the amount of medical data. Studies on how to efficiently compress and store medical text data of increasing patients are in progress. However, previous methods have the shortcoming of compressing medical text data as it is, resulting in low compression rate. This research tries to overcome the problem by using the gamma coding method which enables compression in bit unit. We propose a new compression scheme which encodes the deviations between measured values and normal range values. Furthermore, we suggest to use the previous value with the least deviation from the measurement as the standard value to encode that deviation. Even though the suggested methods are simple, they have high compression rates. Through performance evaluation, we show that the suggested methods are more efficient than the previous methods.

키워드

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