2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)最新文献_第8页

Live image parsing in uterine laparoscopy 子宫腹腔镜实时图像分析

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868106

Ajad Chhatkuli, A. Bartoli, Abed C. Malti, T. Collins

引用次数: 15

Exploring consistent functional brain networks during free viewing of videos via sparse representation 通过稀疏表示在免费观看视频期间探索一致的功能脑网络

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867880

Cheng Lv, Xintao Hu, Junwei Han, Gong Cheng, Xiang Li, Lei Guo, Tianming Liu

引用次数: 2

Myocardium segmentation combining T2 and DE MRI using Multi-Component Bivariate Gaussian mixture model 基于多分量二元高斯混合模型的T2和DE MRI联合心肌分割

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868013

Jie Liu, X. Zhuang, Jing Liu, Shaoting Zhang, Guotai Wang, Lianming Wu, Jianrong Xu, Lixu Gu

引用次数: 5

Functional parcellation of the hippocampus by clustering resting state fMRI signals 静息状态fMRI信号聚类分析海马的功能分割

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867795

Hewei Cheng, Yong Fan

{"title":"Functional parcellation of the hippocampus by clustering resting state fMRI signals","authors":"Hewei Cheng, Yong Fan","doi":"10.1109/ISBI.2014.6867795","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867795","url":null,"abstract":"In this study, we propose a semi-supervised clustering method for parcellating the hippocampus into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented as a graph partition problem by modeling each voxel as one node of the graph and connecting each pair of voxels with an edge weighted by a similarity measure between their functional signals. A geometric parcellation result of the hippocampus is adopted as prior information and a spatial consistent constraint is adopted as a regularization term to achieve spatially contiguous clustering. The graph partition problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated based on resting state fMRI data of 28 subjects for the hippocampus parcellation with three subregions. The experiment results have demonstrated that the proposed method could parcellate the hippocampus into its head, body and tail parts. The distinctive functional and structural connectivity patterns of these subregions, derived from resting state fMRI and dMRI data respectively, have further demonstrated the validity of the parcellation results.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"16 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":"114172281","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

Automatic recognition of fetal standard plane in ultrasound image 超声图像中胎儿标准平面的自动识别

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867815

B. Lei, Liu Zhuo, Siping Chen, Shengli Li, Dong Ni, Tianfu Wang

引用次数: 17

Consistent and robust 4D whole-brain segmentation: Application to traumatic brain injury 一致稳健的4D全脑分割:在颅脑外伤中的应用

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867960

C. Ledig, W. Shi, A. Makropoulos, J. Koikkalainen, R. Heckemann, A. Hammers, J. Lötjönen, O. Tenovuo, D. Rueckert

{"title":"Consistent and robust 4D whole-brain segmentation: Application to traumatic brain injury","authors":"C. Ledig, W. Shi, A. Makropoulos, J. Koikkalainen, R. Heckemann, A. Hammers, J. Lötjönen, O. Tenovuo, D. Rueckert","doi":"10.1109/ISBI.2014.6867960","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867960","url":null,"abstract":"We propose a consistent approach to automatically segmenting longitudinal magnetic resonance scans of pathological brains. Using symmetric intra-subject registration, we align corresponding scans. In an expectation-maximization framework we exploit the availability of probabilistic segmentation estimates to perform a symmetric intensity normalisation. We introduce a novel technique to perform symmetric differential bias correction for images in presence of pathologies. To achieve a consistent multi-time-point segmentation, we propose a patch-based coupling term using a spatially and temporally varying Markov random field. We demonstrate the superior consistency of our method by segmenting repeat scans into 134 regions. Furthermore, the approach has been applied to segment baseline and six month follow-up scans from 56 patients who have sustained traumatic brain injury (TBI). We find significant correlations between regional atrophy rates and clinical outcome: Patients with poor outcome showed a much higher thalamic atrophy rate (4.9 ± 3.4%) than patients with favourable outcome (0.6 ± 1.9%).","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"7 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":"125442240","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

Semi-supervised learning of brain functional networks 脑功能网络的半监督学习

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867794

Yuhui Du, J. Sui, Qingbao Yu, Hao He, V. Calhoun

引用次数: 3

Interactive segmentation of MR images from brain tumor patients 脑肿瘤患者MR图像的交互式分割

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6868007

S. Bauer, N. Porz, Raphael Meier, A. Pica, J. Slotboom, R. Wiest, M. Reyes

引用次数: 3

Contrast enhancement of Micro Dose X-ray images 微剂量x射线图像的对比度增强

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867915

P. Irrera, I. Bloch, M. Delplanque

引用次数: 2

Group-wise connection activation detection based on DICCCOL 基于DICCCOL的分组连接激活检测

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2014-07-31 DOI: 10.1109/ISBI.2014.6867962

Jinglei Lv, Tuo Zhang, Xintao Hu, Dajiang Zhu, Kaiming Li, Lei Guo, Tianming Liu

{"title":"Group-wise connection activation detection based on DICCCOL","authors":"Jinglei Lv, Tuo Zhang, Xintao Hu, Dajiang Zhu, Kaiming Li, Lei Guo, Tianming Liu","doi":"10.1109/ISBI.2014.6867962","DOIUrl":"https://doi.org/10.1109/ISBI.2014.6867962","url":null,"abstract":"Task-based fMRI is widely used to locate activated cortical regions during task performance. In the community of fMRI analysis, the general linear model (GLM) is the most popular method to detect activated brain regions, based on the assumption that fMRI BOLD signals follow well the shape of external stimulus. In this paper, instead of analyzing the voxel-based BOLD signal, we examine the functional connection curves between pairs of brain regions. Specifically, we calculate the dynamic functional connection (DFC) between a pair of our recently developed and validated Dense Individualized and Common Connectivity-based Cortical Landmarks (DICCCOL), and use the GLM to estimate if DFC time series follow the shape of external stimulus. Since the DICCCOL landmarks possess structural and functional correspondence across subjects and these correspondences also apply to their connections, the mixed-effects model is thus performed to effect sizes estimated from GLM of each corresponding connection across subjects to detect group-wise activation. In other words, we assess the activation of cortical landmarks' dynamic interactions at the group-level. Our experimental results demonstrate that the proposed approach is able to detect reasonable activated connection patterns.","PeriodicalId":440405,"journal":{"name":"2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)","volume":"29 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":"126353149","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