메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Li Chen (University of the District of Columbia) V. B. Surya Prasath (University of Missouri)
저널정보
한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.17 No.4
발행연도
2017.12
수록면
235 - 244 (10page)
DOI
10.5391/IJFIS.2017.17.4.235

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
Estimating bone density using mathematical models has direct applications in medical image processing. This paper presents a new measure for bone mineral density analysis based on the dual energy X-ray absorptiometry (DEXA) images. We are proposing an innovative procedure to calculate a scalar value that indicates the connectivity of bone mineral components from DEXA images. This method provides a totally novel measure for bone density study using DEXA scan images that can not only calculate T and Z values and can also determine the quality of the bone in terms of the average intensity of bone density. The new measure proposed is called the λ-measure and it provides new possibilities in terms of finding how well the bone components are connected. We can have λ<SUB>T</SUB><SUB></SUB> and λ<SUB>Z</SUB> corresponding to T and Z scores which augments the traditional values. Combining this method to a λ-connected maximum entropy concept, we obtain good segmentation results. The experiments results and data obtained shows that the new λ-measure should be in the range of [0:962; 0:977].

목차

Abstract
1. Introduction
2. Background
3. Connected Component Segmentation
4. Maximum Entropy Criterion for λ Estimation
5. A New Measure for Bone Connectivity
6. Conclusion
References

참고문헌 (42)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2018-003-001712687