发布求助
文献互助 智能选刊 最新文献

2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro最新文献

筛选
英文 中文
A point based non-rigid registration for tumor resection using iMRI 基于点的非刚性配准的iMRI肿瘤切除术
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490214
Yixun Liu, Chengjun Yao, Liangfu Zhou, N. Chrisochoides
{"title":"A point based non-rigid registration for tumor resection using iMRI","authors":"Yixun Liu, Chengjun Yao, Liangfu Zhou, N. Chrisochoides","doi":"10.1109/ISBI.2010.5490214","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490214","url":null,"abstract":"This paper presents a novel feature point based non-rigid registration of preoperative MRI with resected intra-operative MRI (iMRI) to compensate for brain shift during tumor resection.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122305898","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: 16
Multimodal inference of articulated spine models from higher order energy functions of discrete MRFS 基于离散MRFS高阶能量函数的铰接脊柱模型多模态推断
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490258
S. Kadoury, N. Paragios
{"title":"Multimodal inference of articulated spine models from higher order energy functions of discrete MRFS","authors":"S. Kadoury, N. Paragios","doi":"10.1109/ISBI.2010.5490258","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490258","url":null,"abstract":"In this paper, we introduce a novel approach based on higher order energy functions which have the ability to encode global structural dependencies to infer articulated 3D spine models to CT volume data. A personalized geometrical model is reconstructed from biplanar X-rays before spinal surgery in order to create a spinal column representation which is modeled by a series of intervertebral transformations based on rotation and translation parameters. The shape transformation between the standing and lying poses is then achieved through a Markov Random Field optimization graph, where the unknown variables are the deformations applied to the intervertebral transformations. Singleton and pairwise potentials measure the support from the data and geometrical dependencies between neighboring vertebrae respectively, while higher order cliques are introduced to integrate consistency in regional curves. Optimization of model parameters in a multi-modal context is achieved using efficient linear programming and duality. A qualitative evaluation of the vertebra model alignment obtained from the proposed method gave promising results while the quantitative comparison to expert identification yields an accuracy of 1.8 ± 0.7 mm based on the localization of surgical landmarks.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122897262","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: 5
A systematic performance evaluation of interactive image segmentation methods based on simulated user interaction 基于模拟用户交互的交互式图像分割方法的系统性能评价
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490139
E. Moschidis, J. Graham
{"title":"A systematic performance evaluation of interactive image segmentation methods based on simulated user interaction","authors":"E. Moschidis, J. Graham","doi":"10.1109/ISBI.2010.5490139","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490139","url":null,"abstract":"In this paper we report on the results of a systematic performance evaluation of three efficient image segmentation algorithms. namely Graph-Cuts, Random-Walker and Grow-Cut. The evaluation focuses on their function as the computational part of an interactive segmentation system. The implications caused by the human involvement in the overall process are avoided by simulating two different patterns of user interaction. The methods are evaluated with respect to accuracy, precision, efficiency and parameter sensitivity on three dimensional medical images. The results provide useful insight regarding the algorithmic performance of the selected techniques and the effect of the identified patterns of user interaction on the segmentation outcome.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122905332","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: 25
Ultrasonographic plaque characterization using a rayleigh mixture model 使用瑞利混合模型的超声斑块表征
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490428
J. Seabra, J. Sanches, F. Ciompi, P. Radeva
{"title":"Ultrasonographic plaque characterization using a rayleigh mixture model","authors":"J. Seabra, J. Sanches, F. Ciompi, P. Radeva","doi":"10.1109/ISBI.2010.5490428","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490428","url":null,"abstract":"A correct modelling of tissue morphology is determinant for the identification of vulnerable plaques. This paper aims at describing the plaque composition by means of a Rayleigh Mixture Model applied to ultrasonic data. The effectiveness of using a mixture of distributions is established through synthetic and real ultrasonic data samples. Furthermore, the proposed mixture model is used in a plaque classification problem in Intravascular Ultrasound (IVUS) images of coronary plaques. A classifier tested on a set of 67 in-vitro plaques, yields an overall accuracy of 86% and sensitivity of 92%, 94% and 82%, for fibrotic, calcified and lipidic tissues, respectively. These results strongly suggest that different plaques types can be distinguished by means of the coefficients and Rayleigh parameters of the mixture distribution.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114175324","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
Robust left ventricle segmentation from ultrasound data using deep neural networks and efficient search methods 基于深度神经网络和高效搜索方法的超声数据鲁棒左心室分割
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490181
G. Carneiro, J. Nascimento, A. Freitas
{"title":"Robust left ventricle segmentation from ultrasound data using deep neural networks and efficient search methods","authors":"G. Carneiro, J. Nascimento, A. Freitas","doi":"10.1109/ISBI.2010.5490181","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490181","url":null,"abstract":"The automatic segmentation of the left ventricle of the heart in ultrasound images has been a core research topic in medical image analysis. Most of the solutions are based on low-level segmentation methods, which uses a prior model of the appearance of the left ventricle, but imaging conditions violating the assumptions present in the prior can damage their performance. Recently, pattern recognition methods have become more robust to imaging conditions by automatically building an appearance model from training images, but they present a few challenges, such as: the need of a large set of training images, robustness to imaging conditions not present in the training data, and complex search process. In this paper we handle the second problem using the recently proposed deep neural network and the third problem with efficient searching algorithms. Quantitative comparisons show that the accuracy of our approach is higher than state-of-the-art methods. The results also show that efficient search strategies reduce ten times the run-time complexity.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116618724","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: 40
Non-rigid coregistration of diffusion kurtosis data 扩散峰度数据的非刚性共配准
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490326
J. Veraart, W. Hecke, I. Blockx, A. Linden, M. Verhoye, Jan Sijbers
{"title":"Non-rigid coregistration of diffusion kurtosis data","authors":"J. Veraart, W. Hecke, I. Blockx, A. Linden, M. Verhoye, Jan Sijbers","doi":"10.1109/ISBI.2010.5490326","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490326","url":null,"abstract":"Diffusion kurtosis imaging (DKI) is a relatively new model to study the non-Gaussian behavior of water diffusion in the brain white matter which introduces, besides the conventional diffusion tensor, a 4th order, 3D diffusion kurtosis tensor to describe the diffusion. In this study, a multi-component coregistration algorithm using a viscous fluid model and mutual information is optimized to enable more accurate alignment of the higher order tensor DKI data. The preservation of principle strategy is extended in order to facilitate tensor reorientation of the diffusion and diffusion kurtosis tensors. In addition, experiments demonstrated that involving kurtosis information in the coregistration procedure significantly improves tensor alignment.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128497065","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
Locally weighted Markov random fields for cortical segmentation 皮质分割的局部加权马尔可夫随机场
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490146
M. Cardoso, M. Clarkson, M. Modat, G. Ridgway, S. Ourselin
{"title":"Locally weighted Markov random fields for cortical segmentation","authors":"M. Cardoso, M. Clarkson, M. Modat, G. Ridgway, S. Ourselin","doi":"10.1109/ISBI.2010.5490146","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490146","url":null,"abstract":"Segmenting the human brain from magnetic resonance images is a challenging task due to the convoluted shape of the cortex, noise, intensity non-uniformity and partial volume effects. We propose a new way to overcome part of the bias-variance tradeoff existent in any segmentation technique by locally varying the behaviour of the model. We developed a novel metric based on the Laplacian of the geodesic distance to localise and iteratively modify the prior information and Markov random field weights, leading to a better delineation of deep sulci and narrow gyri. Experiments performed on 20 Brainweb datasets show statistically significant improvements in Dice scores and partial volume estimation when compared to two well established techniques.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128519571","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: 4
Detection and retrieval of cysts in joint ultrasound B-mode and elasticity breast images 关节超声b型和弹性乳房图像中囊肿的检测和恢复
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490387
Jingdan Zhang, S. Zhou, S. Brunke, C. Lowery, D. Comaniciu
{"title":"Detection and retrieval of cysts in joint ultrasound B-mode and elasticity breast images","authors":"Jingdan Zhang, S. Zhou, S. Brunke, C. Lowery, D. Comaniciu","doi":"10.1109/ISBI.2010.5490387","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490387","url":null,"abstract":"Distinguishing cysts from other tumors is a routine clinical practice for diagnosing breast cancer. It has shown that more accurate diagnosis can be achieved by combining elasticity images with traditional B-mode ultrasound images [1]. In this paper, we propose a fully automatic system to detect cysts jointly in both B-mode and elasticity images. It is based on database-guided techniques that learn the knowledge of cyst appearance automatically from B-mode and elasticity images in a database. Further, for a detected cyst in a query image, the cysts with similar image appearance in the database are retrieved to improve diagnostic accuracy and confidence. In the experiment, we show that our system achieves high sensitivity and specificity in cyst diagnosis.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124676580","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: 8
Multi-target tracking of packed yeast cells 包装酵母细胞的多目标跟踪
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490288
R. Delgado-Gonzalo, Nicolas Dénervaud, S. Maerkl, M. Unser
{"title":"Multi-target tracking of packed yeast cells","authors":"R. Delgado-Gonzalo, Nicolas Dénervaud, S. Maerkl, M. Unser","doi":"10.1109/ISBI.2010.5490288","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490288","url":null,"abstract":"The tracking of cell populations in time-lapse microscopy images enables high-throughput spatiotemporal measurements of cell dynamics. In this paper, we present a new algorithm to simultaneously track many cells in crowded areas. The algorithm runs in real time and deals with thousands of cells. The main contribution of this paper is that the algorithm is able to maintain the spatiotemporal consistency of the tracks in crowded areas, even when the temporal resolution is coarse. We validate our approach in terms of its ability to track yeast cells.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124694312","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: 9
Texture analysis in quantitative osteoporosis assessment: Characterizing microarchitecture 定量骨质疏松评估中的纹理分析:表征微结构
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2010-04-14 DOI: 10.1109/ISBI.2010.5490250
A. Valentinitsch, J. Patsch, D. Mueller, F. Kainberger, G. Langs
{"title":"Texture analysis in quantitative osteoporosis assessment: Characterizing microarchitecture","authors":"A. Valentinitsch, J. Patsch, D. Mueller, F. Kainberger, G. Langs","doi":"10.1109/ISBI.2010.5490250","DOIUrl":"https://doi.org/10.1109/ISBI.2010.5490250","url":null,"abstract":"The microarchitecture of the trabecular bone is an highly informative feature for osteoporosis assessment. High resolution peripheral quantitative computed tomography permits its in-vivo observation at a resolution of 82 µm. In this paper we propose an approach that assesses bone microarchitecture based on texture features extracted from the trabecular bone. The method is based on three-dimensional texture features as local descriptors of the structure in the trabecular bone. A clustering in the feature space indicates characteristic classes of microarchitecture that are repeatedly detected across subjects. The distribution of those classes allows for a differentiation between osteoporotic and healthy subjects. We report initial results for the repeatability of the method and its performance for the differentiation of healthy and osteoporotic subjects.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129283768","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: 11
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信