International Journal of Biomedical Imaging最新文献_第10页

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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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

Medical Image Fusion Based on Feature Extraction and Sparse Representation. 基于特征提取和稀疏表示的医学图像融合。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-02-21 DOI: 10.1155/2017/3020461

Yin Fei, Gao Wei, Song Zongxi

{"title":"Medical Image Fusion Based on Feature Extraction and Sparse Representation.","authors":"Yin Fei, Gao Wei, Song Zongxi","doi":"10.1155/2017/3020461","DOIUrl":"https://doi.org/10.1155/2017/3020461","url":null,"abstract":"As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/3020461","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34837712","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: 28

A Novel Histogram Region Merging Based Multithreshold Segmentation Algorithm for MR Brain Images. 一种新的基于直方图区域合并的脑磁共振图像多阈值分割算法。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-03-16 DOI: 10.1155/2017/9759414

Siyan Liu, Xuanjing Shen, Yuncong Feng, Haipeng Chen

引用次数: 10

An Automatic Image Processing System for Glaucoma Screening. 青光眼筛查的自动图像处理系统。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-08-29 DOI: 10.1155/2017/4826385

Ahmed Almazroa, Sami Alodhayb, Kaamran Raahemifar, Vasudevan Lakshminarayanan

{"title":"An Automatic Image Processing System for Glaucoma Screening.","authors":"Ahmed Almazroa, Sami Alodhayb, Kaamran Raahemifar, Vasudevan Lakshminarayanan","doi":"10.1155/2017/4826385","DOIUrl":"https://doi.org/10.1155/2017/4826385","url":null,"abstract":"Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma's population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm's accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm's accuracy. The algorithm's best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/4826385","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35545367","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

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":null,"pages":null},"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

Monte Carlo Simulation for Polychromatic X-Ray Fluorescence Computed Tomography with Sheet-Beam Geometry. 基于板束几何的多色x射线荧光计算机断层扫描蒙特卡罗模拟。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-05-08 DOI: 10.1155/2017/7916260

Shanghai Jiang, Peng He, Luzhen Deng, Mianyi Chen, Biao Wei

{"title":"Monte Carlo Simulation for Polychromatic X-Ray Fluorescence Computed Tomography with Sheet-Beam Geometry.","authors":"Shanghai Jiang, Peng He, Luzhen Deng, Mianyi Chen, Biao Wei","doi":"10.1155/2017/7916260","DOIUrl":"https://doi.org/10.1155/2017/7916260","url":null,"abstract":"X-ray fluorescence computed tomography (XFCT) based on sheet beam can save a huge amount of time to obtain a whole set of projections using synchrotron. However, it is clearly unpractical for most biomedical research laboratories. In this paper, polychromatic X-ray fluorescence computed tomography with sheet-beam geometry is tested by Monte Carlo simulation. First, two phantoms (A and B) filled with PMMA are used to simulate imaging process through GEANT 4. Phantom A contains several GNP-loaded regions with the same size (10 mm) in height and diameter but different Au weight concentration ranging from 0.3% to 1.8%. Phantom B contains twelve GNP-loaded regions with the same Au weight concentration (1.6%) but different diameter ranging from 1 mm to 9 mm. Second, discretized presentation of imaging model is established to reconstruct more accurate XFCT images. Third, XFCT images of phantoms A and B are reconstructed by filter back-projection (FBP) and maximum likelihood expectation maximization (MLEM) with and without correction, respectively. Contrast-to-noise ratio (CNR) is calculated to evaluate all the reconstructed images. Our results show that it is feasible for sheet-beam XFCT system based on polychromatic X-ray source and the discretized imaging model can be used to reconstruct more accurate images.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/7916260","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35047052","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

Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery. 肿瘤切除手术中脑转移的术中成像方式与补偿。

IF 7.6

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-06-05 DOI: 10.1155/2017/6028645

Siming Bayer, Andreas Maier, Martin Ostermeier, Rebecca Fahrig

{"title":"Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery.","authors":"Siming Bayer, Andreas Maier, Martin Ostermeier, Rebecca Fahrig","doi":"10.1155/2017/6028645","DOIUrl":"10.1155/2017/6028645","url":null,"abstract":"Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work.","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/6028645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35142099","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: 57