• Title/Summary/Keyword: Fracture network model

Search Result 83, Processing Time 0.027 seconds

Multi-classification of Osteoporosis Grading Stages Using Abdominal Computed Tomography with Clinical Variables : Application of Deep Learning with a Convolutional Neural Network (멀티 모달리티 데이터 활용을 통한 골다공증 단계 다중 분류 시스템 개발: 합성곱 신경망 기반의 딥러닝 적용)

  • Tae Jun Ha;Hee Sang Kim;Seong Uk Kang;DooHee Lee;Woo Jin Kim;Ki Won Moon;Hyun-Soo Choi;Jeong Hyun Kim;Yoon Kim;So Hyeon Bak;Sang Won Park
    • Journal of the Korean Society of Radiology
    • /
    • v.18 no.3
    • /
    • pp.187-201
    • /
    • 2024
  • Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

Performance Test of Hypocenter Determination Methods under the Assumption of Inaccurate Velocity Models: A case of surface microseismic monitoring (부정확한 속도 모델을 가정한 진원 결정 방법의 성능평가: 지표면 미소지진 모니터링 사례)

  • Woo, Jeong-Ung;Rhie, Junkee;Kang, Tae-Seob
    • Geophysics and Geophysical Exploration
    • /
    • v.19 no.1
    • /
    • pp.1-10
    • /
    • 2016
  • The hypocenter distribution of microseismic events generated by hydraulic fracturing for shale gas development provides essential information for understanding characteristics of fracture network. In this study, we evaluate how inaccurate velocity models influence the inversion results of two widely used location programs, hypoellipse and hypoDD, which are developed based on an iterative linear inversion. We assume that 98 stations are densely located inside the circle with a radius of 4 km and 5 artificial hypocenter sets (S0 ~ S4) are located from the center of the network to the south with 1 km interval. Each hypocenter set contains 25 events placed on the plane. To quantify accuracies of the inversion results, we defined 6 parameters: difference between average hypocenters of assumed and inverted locations, $d_1$; ratio of assumed and inverted areas estimated by hypocenters, r; difference between dip of the reference plane and the best fitting plane for determined hypocenters, ${\theta}$; difference between strike of the reference plane and the best fitting plane for determined hypocenters, ${\phi}$; root-mean-square distance between hypocenters and the best fitting plane, $d_2$; root-mean-square error in horizontal direction on the best fitting plane, $d_3$. Synthetic travel times are calculated for the reference model having 1D layered structure and the inaccurate velocity model for the inversion is constructed by using normal distribution with standard deviations of 0.1, 0.2, and 0.3 km/s, respectively, with respect to the reference model. The parameters $d_1$, r, ${\theta}$, and $d_2$ show positive correlation with the level of velocity perturbations, but the others are not sensitive to the perturbations except S4, which is located at the outer boundary of the network. In cases of S0, S1, S2, and S3, hypoellipse and hypoDD provide similar results for $d_1$. However, for other parameters, hypoDD shows much better results and errors of locations can be reduced by about several meters regardless of the level of perturbations. In light of the purpose to understand the characteristics of hydraulic fracturing, $1{\sigma}$ error of velocity structure should be under 0.2 km/s in hypoellipse and 0.3 km/s in hypoDD.

Groundwater Flow Analysis around Hydraulic Excavation Damaged Zone (수리적 굴착손상영역에서의 지하수유동 특성에 관한 연구)

  • Park, Jong-Sung;Ryu, Dong-Woo;Ryu, Chang-Ha;Lee, Chung-In
    • Tunnel and Underground Space
    • /
    • v.17 no.2 s.67
    • /
    • pp.109-118
    • /
    • 2007
  • The excavation damaged zone (EDZ) is an area around an excavation where in situ rock mass properties, stress condition. displacement. groundwater flow conditions have been altered due to the excavation. Various studies have been carried out on EDZ, but most studies have been focused on the mechanical bahavior of EDZ by in situ experiment. Even though the EDZ could potentially form a high permeable pathway of groundwater flow, only a few studies were performed on the analysis of groundwater flow in EDZ. In this study, the' hydraulic EDZ' was defined as the rock Lone adjacent to the excavation where the hydraulic aperture has been changed due to the excavation. And hydraulic EDZ (hydraulic aperture changed zone) estimated by two-dimensional DEM program was considered in three-dimensional DFN model. From this approach the groundwater flow characteristics corresponding to hydraulic aperture change were examined. Together. a parametric study was performed to examine the boundary conditions that frequently used in DFN analysis such as constant head or constant flux condition. According to the numerical analysis, hydraulic aperture change induced by the hydraulic-mechanical interaction becomes one of the most important factors Influencing the hydraulic behavior of jointed rock masses. And also from this study, we suggest the proper boundary condition in three-dimensional DFN model.