• Title/Summary/Keyword: Multi-atlas

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Automatic Segmentation of Renal Parenchyma using Graph-cuts with Shape Constraint based on Multi-probabilistic Atlas in Abdominal CT Images (복부 컴퓨터 단층촬영영상에서 다중 확률 아틀라스 기반 형상제한 그래프-컷을 사용한 신실질 자동 분할)

  • Lee, Jaeseon;Hong, Helen;Rha, Koon Ho
    • Journal of the Korea Computer Graphics Society
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    • v.22 no.4
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    • pp.11-19
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    • 2016
  • In this paper, we propose an automatic segmentation method of renal parenchyma on abdominal CT image using graph-cuts with shape constraint based on multi-probabilistic atlas. The proposed method consists of following three steps. First, to use the various shape information of renal parenchyma, multi-probabilistic atlas is generated by cortex-based similarity registration. Second, initial seeds for graph-cuts are extracted by maximum a posteriori (MAP) estimation and renal parenchyma is segmented by graph-cuts with shape constraint. Third, to reduce alignment error of probabilistic atlas and increase segmentation accuracy, registration and segmentation are iteratively performed. To evaluate the performance of proposed method, qualitative and quantitative evaluation are performed. Experimental results show that the proposed method avoids a leakage into neighbor regions with similar intensity of renal parenchyma and shows improved segmentation accuracy.

Anterior Cruciate Ligament Segmentation in Knee MRI with Locally-aligned Probabilistic Atlas and Iterative Graph Cuts (무릎 자기공명영상에서 지역적 확률 아틀라스 정렬 및 반복적 그래프 컷을 이용한 전방십자인대 분할)

  • Lee, Han Sang;Hong, Helen
    • Journal of KIISE
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    • v.42 no.10
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    • pp.1222-1230
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    • 2015
  • Segmentation of the anterior cruciate ligament (ACL) in knee MRI remains a challenging task due to its inhomogeneous signal intensity and low contrast with surrounding soft tissues. In this paper, we propose a multi-atlas-based segmentation of the ACL in knee MRI with locally-aligned probabilistic atlas (PA) in an iterative graph cuts framework. First, a novel PA generation method is proposed with global and local multi-atlas alignment by means of rigid registration. Second, with the generated PA, segmentation of the ACL is performed by maximum-aposteriori (MAP) estimation and then by graph cuts. Third, refinement of ACL segmentation is performed by improving shape prior through mask-based PA generation and iterative graph cuts. Experiments were performed with a Dice similarity coefficients of 75.0%, an average surface distance of 1.7 pixels, and a root mean squared distance of 2.7 pixels, which increased accuracy by 12.8%, 22.7%, and 22.9%, respectively, from the graph cuts with patient-specific shape constraints.

Automatic Segmentation of Femoral Cartilage in Knee MR Images using Multi-atlas-based Locally-weighted Voting (무릎 MR 영상에서 다중 아틀라스 기반 지역적 가중투표를 이용한 대퇴부 연골 자동 분할)

  • Kim, Hyeun A;Kim, Hyeonjin;Lee, Han Sang;Hong, Helen
    • Journal of KIISE
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    • v.43 no.8
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    • pp.869-877
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    • 2016
  • In this paper, we propose an automated segmentation method of femoral cartilage in knee MR images using multi-atlas-based locally-weighted voting. The proposed method involves two steps. First, to utilize the shape information to show that the femoral cartilage is attached to a femur, the femur is segmented via volume and object-based locally-weighted voting and narrow-band region growing. Second, the object-based affine transformation of the femur is applied to the registration of femoral cartilage, and the femoral cartilage is segmented via multi-atlas shape-based locally-weighted voting. To evaluate the performance of the proposed method, we compared the segmentation results of majority voting method, intensity-based locally-weighted voting method, and the proposed method with manual segmentation results defined by expert. In our experimental results, the newly proposed method avoids a leakage into the neighboring regions having similar intensity of femoral cartilage, and shows improved segmentation accuracy.

Automatic Meniscus Segmentation from Knee MR Images using Multi-atlas-based Locally-weighted Voting and Patch-based Edge Feature Classification (무릎 MR 영상에서 다중 아틀라스 기반 지역적 가중 투표 및 패치 기반 윤곽선 특징 분류를 통한 반월상 연골 자동 분할)

  • Kim, SoonBeen;Kim, Hyeonjin;Hong, Helen;Wang, Joon Ho
    • Journal of the Korea Computer Graphics Society
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    • v.24 no.4
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    • pp.29-38
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    • 2018
  • In this paper, we propose an automatic segmentation method of meniscus in knee MR images by automatic meniscus localization, multi-atlas-based locally-weighted voting, and patch-based edge feature classification. First, after segmenting the bone and knee articular cartilage, the volume of interest of the meniscus is automatically localized. Second, the meniscus is segmented by multi-atlas-based locally-weighted voting taking into account the weights of shape and intensity distribution in the volume of interest of the meniscus. Finally, to remove leakage to the collateral ligaments with similar intensity, meniscus is refined using patch-based edge feature classification considering shape and distance weights. Dice similarity coefficient between proposed method and manual segmentation were 80.13% of medial meniscus and 80.81 % for lateral meniscus, and showed better results of 7.25% for medial meniscus and 1.31% for lateral meniscus compared to the multi-atlas-based locally-weighted voting.

Hierarchical Organ Segmentation using Location Information based on Multi-atlas in Abdominal CT Images (복부 컴퓨터단층촬영 영상에서 다중 아틀라스 기반 위치적 정보를 사용한 계층적 장기 분할)

  • Kim, Hyeonjin;Kim, Hyeun A;Lee, Han Sang;Hong, Helen
    • Journal of Korea Multimedia Society
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    • v.19 no.12
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    • pp.1960-1969
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    • 2016
  • In this paper, we propose an automatic hierarchical organ segmentation method on abdominal CT images. First, similar atlases are selected using bone-based similarity registration and similarity of liver, kidney, and pancreas area. Second, each abdominal organ is roughly segmented using image-based similarity registration and intensity-based locally weighted voting. Finally, the segmented abdominal organ is refined using mask-based affine registration and intensity-based locally weighted voting. Especially, gallbladder and pancreas are hierarchically refined using location information of neighbor organs such as liver, left kidney and spleen. Our method was tested on a dataset of 12 portal-venous phase CT data. The average DSC of total organs was $90.47{\pm}1.70%$. Our method can be used for patient-specific abdominal organ segmentation for rehearsal of laparoscopic surgery.

Integral effect test for steam line break with coupling reactor coolant system and containment using ATLAS-CUBE facility

  • Bae, Byoung-Uhn;Lee, Jae Bong;Park, Yu-Sun;Kim, Jongrok;Kang, Kyoung-Ho
    • Nuclear Engineering and Technology
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    • v.53 no.8
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    • pp.2477-2487
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    • 2021
  • To improve safety analysis technology for a nuclear reactor containment considering an interaction between a reactor coolant system (RCS) and containment, this study aims at an experimental investigation on the integrated simulation of the RCS and containment, with an integral effect test facility, ATLAS-CUBE. For a realistic simulation of a pressure and temperature (P/T) transient, the containment simulation vessel was designed to preserve a volumetric scale equivalently to the RCS volume scale of ATLAS. Three test cases for a steam line break (SLB) transient were conducted with variation of the initial condition of the passive heat sink or the steam flow direction. The test results indicated a stratified behavior of the steam-gas mixture in the containment following a high-temperature steam injection in prior to the spray injection. The test case with a reduced heat transfer on the passive heat sink showed a faster increase of the P/T inside the containment. The effect of the steam flow direction was also investigated with respect to a multi-dimensional distribution of the local heat transfer on the passive heat sink. The integral effect test data obtained in this study will contribute to validating the evaluation methodology for mass and energy (M/E) and P/T transient of the containment.

Single-Cell Genomics for Investigating Pathogenesis of Inflammatory Diseases

  • Seyoung Jung;Jeong Seok Lee
    • Molecules and Cells
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    • v.46 no.2
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    • pp.120-129
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    • 2023
  • Recent technical advances have enabled unbiased transcriptomic and epigenetic analysis of each cell, known as "single-cell analysis". Single-cell analysis has a variety of technical approaches to investigate the state of each cell, including mRNA levels (transcriptome), the immune repertoire (immune repertoire analysis), cell surface proteins (surface proteome analysis), chromatin accessibility (epigenome), and accordance with genome variants (eQTLs; expression quantitative trait loci). As an effective tool for investigating robust immune responses in coronavirus disease 2019 (COVID-19), many researchers performed single-cell analysis to capture the diverse, unbiased immune cell activation and differentiation. Despite challenges elucidating the complicated immune microenvironments of chronic inflammatory diseases using existing experimental methods, it is now possible to capture the simultaneous immune features of different cell types across inflamed tissues using various single-cell tools. In this review, we introduce patient-based and experimental mouse model research utilizing single-cell analyses in the field of chronic inflammatory diseases, as well as multi-organ atlas targeting immune cells.

Optimization of Multi-Atlas Segmentation with Joint Label Fusion Algorithm for Automatic Segmentation in Prostate MR Imaging

  • Choi, Yoon Ho;Kim, Jae-Hun;Kim, Chan Kyo
    • Investigative Magnetic Resonance Imaging
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    • v.24 no.3
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    • pp.123-131
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    • 2020
  • Purpose: Joint label fusion (JLF) is a popular multi-atlas-based segmentation algorithm, which compensates for dependent errors that may exist between atlases. However, in order to get good segmentation results, it is very important to set the several free parameters of the algorithm to optimal values. In this study, we first investigate the feasibility of a JLF algorithm for prostate segmentation in MR images, and then suggest the optimal set of parameters for the automatic prostate segmentation by validating the results of each parameter combination. Materials and Methods: We acquired T2-weighted prostate MR images from 20 normal heathy volunteers and did a series of cross validations for every set of parameters of JLF. In each case, the atlases were rigidly registered for the target image. Then, we calculated their voting weights for label fusion from each combination of JLF's parameters (rpxy, rpz, rsxy, rsz, β). We evaluated the segmentation performances by five validation metrics of the Prostate MR Image Segmentation challenge. Results: As the number of voxels participating in the voting weight calculation and the number of referenced atlases is increased, the overall segmentation performance is gradually improved. The JLF algorithm showed the best results for dice similarity coefficient, 0.8495 ± 0.0392; relative volume difference, 15.2353 ± 17.2350; absolute relative volume difference, 18.8710 ± 13.1546; 95% Hausdorff distance, 7.2366 ± 1.8502; and average boundary distance, 2.2107 ± 0.4972; in parameters of rpxy = 10, rpz = 1, rsxy = 3, rsz = 1, and β = 3. Conclusion: The evaluated results showed the feasibility of the JLF algorithm for automatic segmentation of prostate MRI. This empirical analysis of segmentation results by label fusion allows for the appropriate setting of parameters.

ANALYSIS OF THE ISP-50 DIRECT VESSEL INJECTION SBLOCA IN THE ATLAS FACILITY WITH THE RELAP5/MOD3.3 CODE

  • Sharabi, Medhat;Freixa, Jordi
    • Nuclear Engineering and Technology
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    • v.44 no.7
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    • pp.709-718
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    • 2012
  • The pressurized water reactor APR1400 adopts DVI (Direct Vessel Injection) for the emergency cooling water in the upper downcomer annulus. The International Standard Problem number 50 (ISP-50) was launched with the aim to investigate thermal hydraulic phenomena during a 50% DVI line break scenario with best estimate codes making use of the experimental data available from the ATLAS facility located at KAERI. The present work describes the calculation results obtained for the ISP-50 using the RELAP5/MOD3.3 system code. The work aims at validation and assessment of the code to reproduce the observed phenomena and investigate about its limitations to predict complicated mixing phenomena between the subcooled emergency cooling water and the two-phase flow in the downcomer. The obtained results show that the overall trends of the main test variables are well reproduced by the calculations. In particular, the pressure in the primary system show excellent agreement with the experiment. The loop seal clearance phenomenon was observed in the calculation and it was found to have an important influence on the transient progression. Moreover, the collapsed water levels in the core are accurately reproduced in the simulations. However, the drop in the downcomer level before the activation of the DVI from safety injection tanks was underestimated due to multi-dimensional phenomena in the downcomer that are not properly captured by one-dimensional simulations.

Breakdown and On-state characteristics of the Multi-RESURF SOI LDMOSFET (Epi층의 농도 및 두께 변화에 따른 Multi-RESURF SOI LDMOSFET의 특성분석)

  • Kim, Hyoung-Woo;Kim, Sang-Cheol;Seo, Kil-Su;Kim, Nam-Kyun;Kim, Eun-Dong
    • Proceedings of the KIEE Conference
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    • 2002.07c
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    • pp.1578-1580
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    • 2002
  • The breakdown and on-state characteristics of the multi-RESURF SOI LDMOSFET is presented. P-/n-epi layer thickness and doping concentration is varied from $2{\mu}m{\sim}5{\mu}m$ and $1{\times}10^{15}/cm^3{\sim}9{\times}10^{15}/cm^3$ to obtain optimum breakdown voltage and on-resistance. The breakdown and on-state characteristics of the device is verified by two-dimensional process simulator ATHENA and device simulator ATLAS.

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