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2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)最新文献

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Noise-adaptive attenuation coefficient estimation in spectral domain optical coherence tomography data 光谱域光学相干层析成像数据的噪声自适应衰减系数估计
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493364
B. Ghafaryasl, Koen A. Vermeer, J. Boer, M. V. Velthoven, L. Vliet
{"title":"Noise-adaptive attenuation coefficient estimation in spectral domain optical coherence tomography data","authors":"B. Ghafaryasl, Koen A. Vermeer, J. Boer, M. V. Velthoven, L. Vliet","doi":"10.1109/ISBI.2016.7493364","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493364","url":null,"abstract":"The attenuation coefficient (AC) is a tissue property that can be estimated from optical coherence tomography (OCT) data. We observed that excessive noise below the retina might cause both an underestimation and a significant variation of the estimated AC values by a state-of-the-art algorithm. Two methods were proposed to reduce these effects: I) by removing the average noise signal from the OCT data; II) by excluding the detected noise region below the retina. The methods were applied to four circular peripapillary retinal scans of a healthy subject. We evaluated all methods quantitatively using metrics for the inter- and intra-A-lines variation of the estimated ACs. Both methods resulted in higher ACs thereby reducing the bias. However, only method II succeeded in reducing the amount of variation by both metrics; method I made things worse. In conclusion, method II yields a more robust and more precise estimate of the AC, in particular for the choroid and sclera, compared to the baseline method.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124773181","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
Recursive water flow: A shape decomposition approach for cell clump splitting 递归水流:细胞团分裂的形状分解方法
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493390
Matthias Dorfer, J. Mattes
{"title":"Recursive water flow: A shape decomposition approach for cell clump splitting","authors":"Matthias Dorfer, J. Mattes","doi":"10.1109/ISBI.2016.7493390","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493390","url":null,"abstract":"We propose a hierarchical method for splitting cell clumps into individual cells which we call Recursive Water Flow (rwf). For the segmentation of cells in histological images we first apply foreground segmentation leading to connected regions of clumping cells. rwf defines one-dimensional cost-functions along paths on the skeleton of these regions. In particular, we collect split-relevant information along geodesic paths between skeleton end-points. This framework allows to exploit combined shape and intensity information for identifying optimal split positions and recursively decomposing the clumps into single distinct cells. Results show that our framework helps to improve cell segmentation performance in contrast to splitting based on local geometrical clues.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128594078","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
Center pixel weight estimation for non-local means filtering using local James-Stein estimator with bounded self-weights 非局部均值滤波的中心像素权估计采用有界自权的局部James-Stein估计
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493216
M. P. Nguyen, S. Chun
{"title":"Center pixel weight estimation for non-local means filtering using local James-Stein estimator with bounded self-weights","authors":"M. P. Nguyen, S. Chun","doi":"10.1109/ISBI.2016.7493216","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493216","url":null,"abstract":"Assigning appropriate center pixel weights (CPW) in nonlocal means (NLM) filter is an important issue to affect the quality of filtered images. Using local James-Stein (LJS) type CPW yielded superior peak signal-to-noise ratio (PSNR) over using other existing methods of determining the contribution of center pixels in NLM. However, the original LJS CPW method assumed no upper bound for self-weights implicitly, it may yield excessively large self-weights and visual artifacts. We propose a method, called bounded self-weights LJS (BLJS), to incorporate bounded self-weights into LJS such that this new estimator is dominating partially. Our proposed method was evaluated using a patient MR image with 3 levels of additive Gaussian noise. For fixed local area, the proposed BLJS yielded lower variances than the original LJS for almost all bias levels. BLJS also achieved PSNR comparable to or better than LJS. Visual image quality assessment showed that BLJS produced less localized visual artifacts than LJS.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132398423","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
Harmonic phase versus sine-wave modulation for measuring regional heart function from tagged MRI images 谐波相位与正弦波调制从标记的MRI图像测量区域心脏功能
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493303
El-Sayed H. Ibrahim, S. Swanson, J. Stojanovska, C. Duvernoy, R. Pop-Busui
{"title":"Harmonic phase versus sine-wave modulation for measuring regional heart function from tagged MRI images","authors":"El-Sayed H. Ibrahim, S. Swanson, J. Stojanovska, C. Duvernoy, R. Pop-Busui","doi":"10.1109/ISBI.2016.7493303","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493303","url":null,"abstract":"Magnetic resonance imaging (MRI) tagging is a valuable technique for evaluating regional heart function. Currently, there are a number of different techniques for analyzing the tagged images. The purpose of this study is to compare the harmonic-phase (HARP) and sine-wave modeling (SinMod) tagging analysis techniques for evaluating myocardial strain and torsion in healthy controls and type-1 diabetes patients. All SinMod measurements were significantly larger than those by HARP (P<;0.001). Nevertheless, there existed consistency in the measurements by each technique, as seen by the good correlation between the HARP and SinMod measurements in both normals (R≥0.52) and patients (R≥0.48), except for apical strain (patients and controls) and mid-ventricular strain in patients. The inter-observer agreement was better in SinMod than in HARP for both torsion and strain (except at apex). In conclusion, under current operating conditions, the results from the two techniques cannot be used interchangeably.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"285 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116605477","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: 2
Supervised partial volume effect unmixing for brain tumor characterization using multi-voxel MR spectroscopic imaging 使用多体素磁共振光谱成像的脑肿瘤表征的监督部分体积效应解混
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493301
Muhammad Asad, Guang Yang, G. Slabaugh
{"title":"Supervised partial volume effect unmixing for brain tumor characterization using multi-voxel MR spectroscopic imaging","authors":"Muhammad Asad, Guang Yang, G. Slabaugh","doi":"10.1109/ISBI.2016.7493301","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493301","url":null,"abstract":"A major challenge faced by multi-voxel Magnetic Resonance Spectroscopy (MV-MRS) imaging is partial volume effect (PVE), where signals from two or more tissue types may be mixed within a voxel. This problem arises due to the low resolution data acquisition, where the size of a voxel is kept relatively large to improve the signal to noise ratio. We propose a novel supervised Signal Mixture Model (SMM), which characterizes the MV-MRS signal into normal, low grade (infiltrative) and high grade (necrotic) brain tissue types, while accounting for in-type variation. An optimization problem is solved based on differential equations, to unmix the tissue by estimating mixture coefficients corresponding to each tissue type at each voxel. This enables visualization of probability heatmaps, useful for characterizing heterogeneous tumors. Experimental results show an overall accuracy of 91.67% and 88.89% for classifying tumors into either low or high grade against histopathology, and demonstrate the method's potential for non-invasive computer-aided diagnosis.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127498502","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: 2
Optimized in vivo conductivity estimation using BEM 利用边界元法优化体内电导率估计
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493375
J. D. Munck, J. Dabek, J. Hulshof
{"title":"Optimized in vivo conductivity estimation using BEM","authors":"J. D. Munck, J. Dabek, J. Hulshof","doi":"10.1109/ISBI.2016.7493375","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493375","url":null,"abstract":"One of the most important factors limiting the accuracy of source localization with EEG is the ignorance of the conductivity of brain, skull and skin. Because these parameters are highly subject dependent, it has been proposed to estimate them in vivo using an electrical impedance tomographic approach. Here the associated conductivity parameter estimation problem is analyzed in the context of different boundary element approaches. The numerical accuracies of the following combinations are compared: double layer and monolayer, linear and constant interpolation. Contrary to the superior behavior of the monolayer approach to predict potentials generated by dipolar sources, for potentials generated by injected currents hardly any improvement was found when comparing the double and monolayer BEM combined with constant potential interpolation. For linear potential interpolation, the numerical accuracy of the double layer approach was found much better than the monolayer approach.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114907317","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: 2
Biology-inspired visualization of morphogenetic motion in the zebrafish endoderm 斑马鱼内胚层形态发生运动的生物学启发可视化
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493416
Konstantin Thierbach, Gopi Shah, I. Glauche, J. Huisken, Ingo Röder, N. Scherf
{"title":"Biology-inspired visualization of morphogenetic motion in the zebrafish endoderm","authors":"Konstantin Thierbach, Gopi Shah, I. Glauche, J. Huisken, Ingo Röder, N. Scherf","doi":"10.1109/ISBI.2016.7493416","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493416","url":null,"abstract":"Effective visualization of large, multidimensional image data is a key instrument for data exploration in biological and medical applications. We propose a method to visualize motion patterns on a spherical surface, illustrated for the example of the zebrafish embryo. In particular, we analyze cellular motion by integrating prior knowledge about the underlying biological process and show how this improves visualization and connects to the conceptional description of the gastrulation process. We conclude that specialized visualizations are necessary to match data representation with conceptional ideas and to get a more intuitive understanding of the design principles of embryonic tissue formation.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114264064","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: 2
An improved hybrid active contour model for nuclear segmentation on breast cancer histopathology 一种用于乳腺癌组织病理学核分割的改进混合活动轮廓模型
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493471
J. Jing, T. Wan, Jiajia Cao, Zengchang Qin
{"title":"An improved hybrid active contour model for nuclear segmentation on breast cancer histopathology","authors":"J. Jing, T. Wan, Jiajia Cao, Zengchang Qin","doi":"10.1109/ISBI.2016.7493471","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493471","url":null,"abstract":"Segmentation of nuclei on breast cancer histopathological images is considered a basic and essential step for diagnosis in a computer-aided diagnosis framework. Nuclear segmentation remains a challenging problem due to the inherent diversity of cancer biology and the variability of the tissue appearance. We present an automatic nuclear segmentation method using an improved hybrid active contour (AC) model driven by both boundary and region information. The initialization of segmentation based on morphological operations and watershed allows for generation of initial closed curves and reduction in computational load of curve evolution for the AC model. Color gradients are computed to capture image gradients along the margin of nucleus. The AC segmentation scheme is performed in a coarse-to-fine fashion which can help to solve the problem of multiple object overlap in an image scene. Segmentation performance was evaluated on various breast cancer histopathological images with different grades and was compared with the existing popular AC models, suggesting that our improved hybrid active contour model can be used to build an accurate and robust nuclear segmentation tool.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127530060","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: 12
Vessel segmentation from quantitative susceptibility maps for local oxygenation venography 局部氧合静脉造影定量敏感性图中的血管分割
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493466
P. Bazin, Victoire Plessis, A. Fan, A. Villringer, C. Gauthier
{"title":"Vessel segmentation from quantitative susceptibility maps for local oxygenation venography","authors":"P. Bazin, Victoire Plessis, A. Fan, A. Villringer, C. Gauthier","doi":"10.1109/ISBI.2016.7493466","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493466","url":null,"abstract":"Recent works have demonstrated that oxygenation in the brain can be measured via susceptibility shifts between vessels and neighboring regions in magnetic resonance images. To obtain a rich picture of local oxygenation, small venous vessels across the cortex need to be extracted. This work presents a novel vessel filter for the segmentation of vasculature in high resolution quantitative susceptibility mapping. The filter recursively estimates image ridges, resulting in highly specific responses. A global probability diffusion scheme further enhances the response along connected vessels while removing inconsistent ones. Vessel diameters are then estimated in order to refine the segmentation and model partial volume effects.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124331090","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: 24
Discovering true association between multimodal data sets using structured and sparse canonical correlation analysis: A simulation study 使用结构化和稀疏典型相关分析发现多模态数据集之间的真正关联:模拟研究
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2016-06-16 DOI: 10.1109/ISBI.2016.7493392
A. Mohammadi-Nejad, G. Hossein-Zadeh, H. Soltanian-Zadeh
{"title":"Discovering true association between multimodal data sets using structured and sparse canonical correlation analysis: A simulation study","authors":"A. Mohammadi-Nejad, G. Hossein-Zadeh, H. Soltanian-Zadeh","doi":"10.1109/ISBI.2016.7493392","DOIUrl":"https://doi.org/10.1109/ISBI.2016.7493392","url":null,"abstract":"Recently, multi-modal data fusion emerged as a comprehensive approach in the field of neuroimaging. As a multivariate approach, canonical correlation analysis (CCA) is frequently used for data fusion. However, the current CCA-based fusion approaches face many problems in the sense of high-dimensionality, multi-colinearity, unimodal feature selection, asymmetric and reshaping of the imaging data into vectors. In this paper, we propose a structured and sparse CCA (ssCCA) technique to overcome the above problems. To investigate the performance of the proposed approach, we compared three multivariate and multi-modal fusion techniques: standard CCA, regularized sparse CCA, and ssCCA, with respect to their ability to detect multi-modal data associations. The results demonstrate that the ssCCA approach has superior recovery performance in the extraction of the true correlated variables relative to the other two fusion approaches.","PeriodicalId":338348,"journal":{"name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130646014","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
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