International Journal of Biomedical Imaging最新文献_第8页

Saliency-Based Bleeding Localization for Wireless Capsule Endoscopy Diagnosis. 基于显著性的无线胶囊内窥镜出血定位诊断。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-11-28 DOI: 10.1155/2017/8147632

Hongda Chen, Shaoze Wang, Yong Ding, Dahong Qian

引用次数: 4

Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images. 基于稀疏码本模型的多相医学图像局部结构检索。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-02-13 DOI: 10.1155/2017/1413297

Jian Wang, Xian-Hua Han, Yingying Xu, Lanfen Lin, Hongjie Hu, Chongwu Jin, Yen-Wei Chen

{"title":"Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images.","authors":"Jian Wang, Xian-Hua Han, Yingying Xu, Lanfen Lin, Hongjie Hu, Chongwu Jin, Yen-Wei Chen","doi":"10.1155/2017/1413297","DOIUrl":"https://doi.org/10.1155/2017/1413297","url":null,"abstract":"Characterization and individual trait analysis of the focal liver lesions (FLL) is a challenging task in medical image processing and clinical site. The character analysis of a unconfirmed FLL case would be expected to benefit greatly from the accumulated FLL cases with experts' analysis, which can be achieved by content-based medical image retrieval (CBMIR). CBMIR mainly includes discriminated feature extraction and similarity calculation procedures. Bag-of-Visual-Words (BoVW) (codebook-based model) has been proven to be effective for different classification and retrieval tasks. This study investigates an improved codebook model for the fined-grained medical image representation with the following three advantages: (1) instead of SIFT, we exploit the local patch (structure) as the local descriptor, which can retain all detailed information and is more suitable for the fine-grained medical image applications; (2) in order to more accurately approximate any local descriptor in coding procedure, the sparse coding method, instead of K-means algorithm, is employed for codebook learning and coded vector calculation; (3) we evaluate retrieval performance of focal liver lesions (FLL) using multiphase computed tomography (CT) scans, in which the proposed codebook model is separately learned for each phase. The effectiveness of the proposed method is confirmed by our experiments on FLL retrieval.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"1413297"},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/1413297","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34812206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Future of the Renal Biopsy: Time to Change the Conventional Modality Using Nanotechnology. 肾活检的未来：利用纳米技术改变传统检查方式的时候到了。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-02-19 DOI: 10.1155/2017/6141734

Hamid Tayebi Khosroshahi, Behzad Abedi, Sabalan Daneshvar, Yashar Sarbaz, Abolhassan Shakeri Bavil

引用次数: 0

Evaluation of Deformable Image Registration for Three-Dimensional Temporal Subtraction of Chest Computed Tomography Images. 可变形图像配准对胸部ct图像三维时间相减的评价。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-10-12 DOI: 10.1155/2017/3457189

Ping Yan, Yoshie Kodera, Kazuhiro Shimamoto

{"title":"Evaluation of Deformable Image Registration for Three-Dimensional Temporal Subtraction of Chest Computed Tomography Images.","authors":"Ping Yan, Yoshie Kodera, Kazuhiro Shimamoto","doi":"10.1155/2017/3457189","DOIUrl":"https://doi.org/10.1155/2017/3457189","url":null,"abstract":"Purpose: To perform lung image registration for reducing misregistration artifacts on three-dimensional (3D) temporal subtraction of chest computed tomography (CT) images, in order to enhance temporal changes in lung lesions and evaluate these changes after deformable image registration (DIR).Methods: In 10 cases, mutual information (MI) lung mask affine mapping combined with cross-correlation (CC) lung diffeomorphic mapping was used to implement lung volume registration. With advanced normalization tools (ANTs), we used greedy symmetric normalization (greedy SyN) as a transformation model, which involved MI-CC-SyN implementation. The resulting displacement fields were applied to warp the previous (moving) image, which was subsequently subtracted from the current (fixed) image to obtain the lung subtraction image.Results: The average minimum and maximum log-Jacobians were 0.31 and 3.74, respectively. When considering 3D landmark distance, the root-mean-square error changed from an average of 20.82 mm for Pfixed to Pmoving to 0.5 mm for Pwarped to Pfixed. Clear shadows were observed as enhanced lung nodules and lesions in subtraction images. The lesion shadows showed lesion shrinkage changes over time. Lesion tissue morphology was maintained after DIR.Conclusions: DIR (greedy SyN) effectively and accurately enhanced temporal changes in chest CT images and decreased misregistration artifacts in temporal subtraction images.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"3457189"},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/3457189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35628394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Multitasking Electrical Impedance Tomography System Using Titanium Alloy Electrode. 钛合金电极多任务电阻抗层析成像系统。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-10-31 DOI: 10.1155/2017/3589324

Abdalla Salama, Amin Malekmohammadi, Shahram Mohanna, Rajprasad Rajkumar

引用次数: 2

Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM. 基于MRI的脑肿瘤检测图像分析及生物启发BWT和SVM特征提取。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-03-06 DOI: 10.1155/2017/9749108

Nilesh Bhaskarrao Bahadure, Arun Kumar Ray, Har Pal Thethi

{"title":"Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM.","authors":"Nilesh Bhaskarrao Bahadure, Arun Kumar Ray, Har Pal Thethi","doi":"10.1155/2017/9749108","DOIUrl":"https://doi.org/10.1155/2017/9749108","url":null,"abstract":"The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 96.51% accuracy, 94.2% specificity, and 97.72% sensitivity, demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 0.82 dice similarity index coefficient, which indicates better overlap between the automated (machines) extracted tumor region with manually extracted tumor region by radiologists. The simulation results prove the significance in terms of quality parameters and accuracy in comparison to state-of-the-art techniques.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"9749108"},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/9749108","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34877145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 446

Corrigendum to "Automatic Characterization of the Physiological Condition of the Carotid Artery in 2D Ultrasound Image Sequences Using Spatiotemporal and Spatiospectral 2D Maps". “使用时空和空间光谱二维地图在二维超声图像序列中自动表征颈动脉生理状况”的勘误表。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-06-28 DOI: 10.1155/2017/4237858

Hamed Hamid Muhammed, Jimmy C Azar

引用次数: 0

An Improved Extrapolation Scheme for Truncated CT Data Using 2D Fourier-Based Helgason-Ludwig Consistency Conditions. 基于二维傅里叶Helgason-Ludwig一致性条件的截断CT数据改进外推方案。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-07-20 DOI: 10.1155/2017/1867025

Yan Xia, Martin Berger, Sebastian Bauer, Shiyang Hu, Andre Aichert, Andreas Maier

{"title":"An Improved Extrapolation Scheme for Truncated CT Data Using 2D Fourier-Based Helgason-Ludwig Consistency Conditions.","authors":"Yan Xia, Martin Berger, Sebastian Bauer, Shiyang Hu, Andre Aichert, Andreas Maier","doi":"10.1155/2017/1867025","DOIUrl":"https://doi.org/10.1155/2017/1867025","url":null,"abstract":"We improve data extrapolation for truncated computed tomography (CT) projections by using Helgason-Ludwig (HL) consistency conditions that mathematically describe the overlap of information between projections. First, we theoretically derive a 2D Fourier representation of the HL consistency conditions from their original formulation (projection moment theorem), for both parallel-beam and fan-beam imaging geometry. The derivation result indicates that there is a zero energy region forming a double-wedge shape in 2D Fourier domain. This observation is also referred to as the Fourier property of a sinogram in the previous literature. The major benefit of this representation is that the consistency conditions can be efficiently evaluated via 2D fast Fourier transform (FFT). Then, we suggest a method that extrapolates the truncated projections with data from a uniform ellipse of which the parameters are determined by optimizing these consistency conditions. The forward projection of the optimized ellipse can be used to complete the truncation data. The proposed algorithm is evaluated using simulated data and reprojections of clinical data. Results show that the root mean square error (RMSE) is reduced substantially, compared to a state-of-the-art extrapolation method.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"1867025"},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/1867025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35321534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast. 压缩感知动态增强乳房MRI中时间正则化的定量评价。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-08-28 DOI: 10.1155/2017/7835749

Dong Wang, Lori R Arlinghaus, Thomas E Yankeelov, Xiaoping Yang, David S Smith

{"title":"Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast.","authors":"Dong Wang, Lori R Arlinghaus, Thomas E Yankeelov, Xiaoping Yang, David S Smith","doi":"10.1155/2017/7835749","DOIUrl":"https://doi.org/10.1155/2017/7835749","url":null,"abstract":"Purpose: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast.Methods: We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (TGV α2), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters Ktrans (volume transfer constant) and ve (extravascular-extracellular volume fraction) across a population of random sampling schemes.Results: NN produced the lowest image error (SER: 29.1), while TV/TGV α2 produced the most accurate Ktrans (CCC: 0.974/0.974) and ve (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate Ktrans (CCC: 0.842) and ve (CCC: 0.799).Conclusion: TV/TGV α2 should be used as temporal constraints for CS DCE-MRI of the breast.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"7835749"},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/7835749","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35373103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Computer-Aided Cobb Measurement Based on Automatic Detection of Vertebral Slopes Using Deep Neural Network. 基于深度神经网络的椎体坡度自动检测的计算机辅助Cobb测量。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-10-03 DOI: 10.1155/2017/9083916

Junhua Zhang, Hongjian Li, Liang Lv, Yufeng Zhang

{"title":"Computer-Aided Cobb Measurement Based on Automatic Detection of Vertebral Slopes Using Deep Neural Network.","authors":"Junhua Zhang, Hongjian Li, Liang Lv, Yufeng Zhang","doi":"10.1155/2017/9083916","DOIUrl":"https://doi.org/10.1155/2017/9083916","url":null,"abstract":"Objective: To develop a computer-aided method that reduces the variability of Cobb angle measurement for scoliosis assessment.Methods: A deep neural network (DNN) was trained with vertebral patches extracted from spinal model radiographs. The Cobb angle of the spinal curve was calculated automatically from the vertebral slopes predicted by the DNN. Sixty-five in vivo radiographs and 40 model radiographs were analyzed. An experienced surgeon performed manual measurements on the aforementioned radiographs. Two examiners used both the proposed and the manual measurement methods to analyze the aforementioned radiographs.Results: For model radiographs, the intraclass correlation coefficients were greater than 0.98, and the mean absolute differences were less than 3°. This indicates that the proposed system showed high repeatability for measurements of model radiographs. For the in vivo radiographs, the reliabilities were lower than those from the model radiographs, and the differences between the computer-aided measurement and the manual measurement by the surgeon were higher than 5°.Conclusion: The variability of Cobb angle measurements can be reduced if the DNN system is trained with enough vertebral patches. Training data of in vivo radiographs must be included to improve the performance of DNN.Significance: Vertebral slopes can be predicted by DNN. The computer-aided system can be used to perform automatic measurements of Cobb angle, which is used to make reliable and objective assessments of scoliosis.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"9083916"},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/9083916","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35536423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 52