2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)最新文献_第9页

Automatic blood pool identification in contrast ultrasound using principal component analysis 主成分分析在对比超声中的自动血池识别

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868083

S. Saporito, Ingeborg H. F. Herold, P. Houthuizen, H. Korsten, H. C. Assen, M. Mischi

引用次数: 1

Image reconstruction by electrical impedance tomography using multi-objective simulated annealing 基于多目标模拟退火的电阻抗断层成像图像重建

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867840

Thiago de C. Martins, A. Fernandes, M. Tsuzuki

引用次数: 15

Superslicing frame restoration for anisotropic sstem 各向异性系统的超拼接帧恢复

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868090

D. Laptev, A. Veznevets, J. Buhmann

引用次数: 2

Cortical parcellation for neonatal brains 新生儿大脑皮层包裹

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868134

Jue Wu, M. Ashtari, L. Betancourt, N. Brodsky, J. Giannetta, J. Gee, H. Hurt, B. Avants

引用次数: 6

Data driven editing of RIB centerlines 数据驱动的编辑肋骨中心线

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867820

N. El-Zehiry, A. Wimmer

{"title":"Data driven editing of RIB centerlines","authors":"N. El-Zehiry, A. Wimmer","doi":"10.1109/ISBI.2014.6867820","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867820","url":null,"abstract":"Rib Unfolding refers to the flattening of the rib cage into a two dimensional image that enables the radiologist to quickly examine all ribs for metastases and fractures without having to scroll through every single image in the CT scans. The rib centerline extraction is the core component of the rib unfolding technology. If the computed centerlines deviate from the true centerlines of the ribs then the unfolding shows the bone cortex or even surrounding tissues, making it impossible to spot lesions inside the ribs. Therefore, this paper presents an interactive system for data driven editing of rib centerlines. The user simply has to place a click point at the center of a rib. From there, the centerline is automatically corrected in both directions until the distance to the old one is below a threshold. We formulate the interactive data driven editing as an energy minimization problem where the new centerline point is calculated as the center of mass of the segmentation mask in the plane orthogonal to the rib centerline, this segmentation mask represent the rib cross section. An automatic tracing scheme is calculated based on the refined centerline point and along the tangent vector to the refined centerlines to get the next orthogonal plane to be segmented. The novelty of this paper is three fold: 1. It defines an intuitive minimal user interaction workflow for the correction of rib centerlines. 2. It uses the data in the neighborhood of the centerline point to formulate the energy minimization problem and obtain a more accurate segmentation. 3. We present a novel re-initialization component to prevent the rib tracing from deviating from the correct solution. The initial point to be corrected is re-initialized based on the neighboring ribs. Quantitative assessment of our method shows that in 85% percent of the cases the rib correction can be perfomed using one or two points.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128336048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A robust and extendable framework towards fully automated diagnosis of nonmass lesions in breast DCE-MRI 对乳腺DCE-MRI非肿块性病变全自动诊断的一个强大且可扩展的框架

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867826

Lei Wang, M. Harz, T. Böhler, B. Platel, A. Homeyer, H. Hahn

{"title":"A robust and extendable framework towards fully automated diagnosis of nonmass lesions in breast DCE-MRI","authors":"Lei Wang, M. Harz, T. Böhler, B. Platel, A. Homeyer, H. Hahn","doi":"10.1109/ISBI.2014.6867826","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867826","url":null,"abstract":"Diagnosis of breast nonmass lesions, most notably ductal carcinoma in situ, is challenging. Recent studies show that dynamic contrast enhanced MRI achieves high sensitivity in diagnosis of nonmass lesions. Unlike successfully applied to diagnose mass lesions, particularly kinetic features are reported to be less effective in discriminating nonmass lesions. It is even difficult for human observers to differentiate nonmass lesions against the enhancing parenchymal or benign lesions due to their sometimes similar morphology and contrast kinetics. Towards an automated computer-aided diagnosis system of nonmass lesions, we implemented an extendable and completely automated framework that is efficient and modularized, aiming to discriminate detected suspicious regions into malignant and benign. The entire framework consists of five sequentially executed modules: motion correction, segmentation of breast regions, detection of suspicious regions, feature extraction, and knowledge-based analysis of suspicious regions. A preliminary test was performed on a data set collecting 162 nonmass lesions extracted from 67 patients, which achieved an area under ROC curve value of 0.74 for malignant lesions.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124629550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Calibration image pre-processing in 3D body surface measurement system 三维体表测量系统标定图像预处理

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867922

Xinran Liu, Ping Zhou, Tongjing Zhu

引用次数: 1

Sparsity-based PET image reconstruction using MRI learned dictionaries 基于稀疏性的PET图像重建利用MRI学习字典

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868063

Jing Tang, Yanhua Wang, R. Yao, L. Ying

{"title":"Sparsity-based PET image reconstruction using MRI learned dictionaries","authors":"Jing Tang, Yanhua Wang, R. Yao, L. Ying","doi":"10.1109/ISBI.2014.6868063","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6868063","url":null,"abstract":"Incorporating anatomical information obtained by magnetic resonance (MR) imaging has shown its promises to improve the positron emission tomography (PET) imaging quality. In this paper, we propose a novel maximum a posteriori (MAP) PET image reconstruction technique using a sparse prior whose dictionary is learned from the corresponding MR images. Specifically, a PET image is divided into three-dimensional overlapping patches which are expected to be sparsely represented over a redundant dictionary. With the assumption that the PET and MR images of a patient can be sparsified under a common dictionary, the dictionary is learned from the MR image to involve anatomical measurement in PET image reconstruction. The PET image and its sparse representation are updated alternately in the iterative reconstruction process. We evaluated the performance of the proposed method quantitatively, using a realistic simulation with the BrainWeb database phantoms. Noticeable improvement on the noise versus bias tradeoff has been demonstrated in images reconstructed from the proposed method, compared to that from the conventional smoothness MAP method.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131045986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Integrating group-wise functional brain activities via point processes 通过点过程整合群体智慧的功能性大脑活动

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867959

Xi Jiang, Jinglei Lv, Dajiang Zhu, Tuo Zhang, Xintao Hu, Lei Guo, Tianming Liu

引用次数: 6

Biomechanical kidney model for predicting tumor displacement in the presence of external pressure load 体外压力负荷下预测肿瘤移位的生物力学肾脏模型

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867994

Ivan Figueroa-Garcia, J. Peyrat, G. Hamarneh, R. Abugharbieh

{"title":"Biomechanical kidney model for predicting tumor displacement in the presence of external pressure load","authors":"Ivan Figueroa-Garcia, J. Peyrat, G. Hamarneh, R. Abugharbieh","doi":"10.1109/ISBI.2014.6867994","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867994","url":null,"abstract":"Robot-assisted partial nephrectomy (RAPN) is a minimally invasive surgery for the treatment of renal cell carcinoma that consists of removing the portion of the kidney that contains the tumor. To plan the resection, surgeons rely on preoperative scans of the patient. However, at surgery time, the shape of abdominal organs differ from these images due to factors such as patient position, insufflation and manipulation with surgical instruments. In this work, we focus on the simulation of kidney deformation due to an external pressure load, e.g. during insufflation, to provide a better estimation of the tumor mass position that is particularly important to plan resection with proper margins. The CT scans of ex vivo lamb kidneys with artificial tumors and fiducials are acquired in absence of external pressure load. From these images, 3D tetra-hedral meshes of kidney parenchyma and tumor, as well as a triangular mesh of the capsule, are extracted and then used along with a soft tissue biomechanical model to simulate deformations under additional external pressure load. A second CT scan of the same kidneys under real pressure load are acquired as a reference to evaluate the advantage of simulating deformations over using the first CT scan without external pressure load. Results show that the biomechanical simulation improves by 29% the tumor localization.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133297937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10