서지주요정보
Resolution enhancement of low-resolution skeletal images through reconstructing bone microstructure using topology optimization = 위상최적설계 기반의 골 미세구조 재구성을 통한 저해상도 골격계 영상의 고해상화
서명 / 저자 Resolution enhancement of low-resolution skeletal images through reconstructing bone microstructure using topology optimization = 위상최적설계 기반의 골 미세구조 재구성을 통한 저해상도 골격계 영상의 고해상화 / Jung Jin Kim.
발행사항 [대전 : 한국과학기술원, 2019].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8033299

소장위치/청구기호

학술문화관(문화관) 보존서고

DGT 19002

휴대폰 전송

도서상태

이용가능(대출불가)

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반납예정일

리뷰정보

초록정보

Although high-resolution skeletal images are essential for accurate bone strength assessment, the current HR imaging modalities have critical problems that remain to be solved such as high radiation doses, low signal-to-noise ratios, and long scan times. Resolution enhancement techniques, which have recently received much attention, have also been difficult to obtain acceptable image resolutions. Inspired by the self-optimizing capabilities of bone (i.e. reorienting the trabecula for maximum mechanical efficiency with minimum bone mass), this dissertation proposes the novel resolution enhancement of low-resolution skeletal images through reconstructing bone microstructure using topology optimization. For the purpose, a fully automated segmentation using the patient-specific optimal thresholding and watershed algorithm firstly is proposed for extracting a target bone from medical scan data. Using the golden section method and load path algorithm, the proposed method first determines the patient-specific optimal threshold value that enables reliably separating two bones in a joint while removing cortical and trabecular bone in the femur at the minimum. This provides regional information on the femur. The watershed algorithm is then used to obtain boundary information on a target bone. The target bone can be extracted by merging the complementary information on a target image. For eight proximal femur CT images, compared with the manual segmentation and other segmentation methods, the proposed method offers a high accuracy in terms of the dice overlap coefficient and average surface distance within a fast timeframe in terms of processing time per slice. The proposed method also delivers structural behavior which is close to that of the manual segmentation with a small mean of average relative errors of the risk factor. Secondly, estimation of local bone loads for the volume of interest is proposed in order to reduce excessive computational cost in the finite element analysis. The proposed method obtains physiological local load through partitioning and static condensation of a localized finite element model. The method is verified for the three VOI in a proximal femur in terms of force equilibrium, displacement field, and strain energy density (SED) distribution. The effect of the global load deviation on the local load estimation is also investigated by perturbing a hip joint contact force (HCF) in the femoral head. Deviation in force magnitude exhibits the greatest absolute changes in a SED distribution due to its own greatest deviation, whereas angular deviation perpendicular to a HCF provides the greatest relative change. Thirdly, topology optimization-based bone microstructure reconstruction is proposed to enhance resolution of LR images. The proposed method conducts mesh refinement for resolution upscaling and then performs topology optimization with a constraint for the density deviation at multiresolution in order to preserve the subject-specific bone distribution data. The reconstructed trabecular bone includes the characteristic trabecular patterns and has morphometric indices that are in good agreement with the anatomical data in the literature. As for computational efficiency, the localization for the VOI reduces the number of FEs by 99%, compared with that of the full FE model. Compared with the previous single resolution density deviation constraint, the proposed multiresolution density deviation constraints enable at least 65% and 47% reductions in the number of iterations and computing time, respectively. Finally, topology optimization-based bone microstructure reconstruction is validated. For the purpose, the proposed method used clinical QCT images and a micro-CT image. First, this study investigates whether the method can represent general bone characteristic pattern and age-related morphology difference. The bone strength difference between the LR input and the HR reconstructed images is investigated. Then, the method is thoroughly validated by comparing the reconstructed image and its reference image. The results demonstrate that the proposed method can reconstruct bone microstructure that has almost the same bone strength (maximum error is 1%) as well as bone morphology (maximum error 4% except SMI)

고해상도 골격 이미지는 정확한 골 강도 평가에 필수적이지만 현재의 고해상화 영상 장치는 높은 방사선량, 낮은 신호 대 잡음비, 긴 스캔 시간과 같은 해결해야 할 중요한 문제를 가지고 있습니다. 최근 많은 관심을 받은 해상도 향상 기술 또한 허용 가능한 이미지 해상도를 얻기가 어려운 상황입니다. 이 논문은 골 자체 최적화 기능 (최소 뼈 질량으로 기계적 효율을 최대화하기 위해 뼈의 방향을 재조정)에 의해 영감을 얻어 위상최적설계를 사용하여 뼈의 골 미세구조를 재구성 함으로써 저해상도 골격 이미지의 고해상화할 수 있는 방법을 제안합니다.

서지기타정보

서지기타정보
청구기호 {DGT 19002
형태사항 93 p. : 삽화 ; 30 cm
언어 영어
일반주기 저자명의 한글표기 : 김정진
지도교수의 영문표기 : In Gwun Jang
지도교수의 한글표기 : 장인권
Appendix: A, Determination of the patient-specific optimal threshold using the golden section method and load path algorithm. - B, Watershed algorithm
학위논문 학위논문(박사) - 한국과학기술원 : 조천식녹색교통대학원,
서지주기 References : p.79-86
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