2013 IEEE 10th International Symposium on Biomedical Imaging最新文献_第3页

Sparse magnetic resonance imaging using tagging RF pulses 稀疏磁共振成像使用标记射频脉冲

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556472

V. Singh, A. Tewfik

{"title":"Sparse magnetic resonance imaging using tagging RF pulses","authors":"V. Singh, A. Tewfik","doi":"10.1109/ISBI.2013.6556472","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556472","url":null,"abstract":"Few fast magnetic resonance (MR) imaging techniques have proposed modifications to the MR signal encoding formulation in order to improve the performance guarantees of image recovery using compressed sensing. A limitation of the previously proposed encoding formulations is their difficult realization on the physical hardware. The deviation of realizable formulation from the theoretical model leads to operating characteristics which are clinically infeasible. In this paper, a novel MR signal encoding formulation using tagging radio-frequency pulses is proposed. The proposed formulation uses tagging pulses to uniquely modulate the longitudinal magnetization in the field-of-view for each MR excitation. The modulation of magnetization leads to mixing of information in the spatial Fourier space which improves the incoherence between the sensing and the sparsifying basis. The physical realization of the proposed formulation is promising due to the use of clinically active RF pulses. The preliminary results for image recovery experiments using the proposed formulation on an in-vivo dataset are comparably close and at times better than the results of the difficult-to-realize state-of-the-art formulation.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131551600","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: 0

An automated drusen detection system for classifying age-related macular degeneration with color fundus photographs 用彩色眼底照片分类老年性黄斑变性的自动检测系统

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556807

Yuanjie Zheng, B. Vanderbeek, Ebenezer Daniel, D. Stambolian, M. Maguire, D. Brainard, J. Gee

引用次数: 32

Boundary detection in echocardiography using a Split Bregman edge detector and a topology preserving level set approach 超声心动图的边界检测使用分裂Bregman边缘检测器和拓扑保持水平集方法

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556415

N. Duggan, Hayden Schaeffer, C. L. Guyader, E. Jones, M. Glavin, L. Vese

引用次数: 2

Efficient extraction of 3D bone cells descriptors from micro-CT images 微ct图像中三维骨细胞描述符的高效提取

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556817

Pei Dong, S. Haupert, P. Gouttenoire, F. Peyrin

引用次数: 2

Validation of a non-rigid registration method for motion compensation in 4D ultrasound of the liver 肝脏四维超声运动补偿的非刚性配准方法验证

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556594

S. Vijayan, S. Klein, E. F. Hofstad, F. Lindseth, B. Ystgaard, T. Langø

{"title":"Validation of a non-rigid registration method for motion compensation in 4D ultrasound of the liver","authors":"S. Vijayan, S. Klein, E. F. Hofstad, F. Lindseth, B. Ystgaard, T. Langø","doi":"10.1109/ISBI.2013.6556594","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556594","url":null,"abstract":"Future therapy using focused ultrasound (FUS) to treat tumors in abdominal organs, such as the liver, must incorporate motion tracking of these organs due to breathing and drift caused by gravity and intestines (peristalsis). Motion tracking of the target (e.g. tumor) is needed to ensure accurately located sonications. We have performed a quantitative validation of a methodology for motion tracking of the liver with 4D (3D+time) ultrasound. The offline analysis was done using a recently published non-rigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D sequence in a group-wise optimization fashion, thus avoiding a bias towards a specifically chosen reference time point. Both spatial and temporal smoothness of the transformations are enforced by using a 4D free-form B-spline deformation model. For our evaluation, three healthy volunteers were scanned over several breath cycles from three different positions and angles on the abdomen (totally nine 4D scans). A skilled physician performed the scanning and manually annotated well-defined anatomic landmarks for assessment of the automatic algorithm. Four engineers each annotated these points in all time frames, the mean of which was taken as a gold standard. The error of the automatic motion estimation method was compared with inter-observer variability. The registration method estimated liver motion better than the observers and had an error (75% percentile over all datasets) of 1 mm. We conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131242862","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: 26

Assessment of cancer therapy effects using texton-based characterization of quantitative ultrasound parametric images 利用基于文本的定量超声参数图像表征来评估癌症治疗效果

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556788

M. Gangeh, A. Sadeghi-Naini, M. Kamel, G. Czarnota

引用次数: 23

Automatic notch detection in retinal images 视网膜图像中的自动缺口检测

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556805

Mei Hui Tan, Ying Sun, S. Ong, Jiang Liu, M. Baskaran, T. Aung, T. Wong

引用次数: 18

3D Haar-like elliptical features for object classification in microscopy 三维haar样椭圆特征在显微镜下的物体分类

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556694

F. Amat, Philipp J. Keller

引用次数: 6

Automatic dendrite spines detection from x-ray tomography volumes 从x射线断层扫描体积中自动检测树突棘

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556505

X. Descombes, G. Malandain, C. Fonta, László Négyessy, R. Mokso

引用次数: 2

Functional connectivity eigennetworks reveal different brain dynamics in multiple sclerosis patients 功能连接特征网络揭示多发性硬化症患者不同的脑动力学

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556528

Nora Leonardi, J. Richiardi, D. Ville

引用次数: 10