International Journal of Biomedical Imaging最新文献

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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,&nbsp;Martin Berger,&nbsp;Sebastian Bauer,&nbsp;Shiyang Hu,&nbsp;Andre Aichert,&nbsp;Andreas Maier","doi":"10.1155/2017/1867025","DOIUrl":"https://doi.org/10.1155/2017/1867025","url":null,"abstract":"<p><p>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.</p>","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,&nbsp;Lori R Arlinghaus,&nbsp;Thomas E Yankeelov,&nbsp;Xiaoping Yang,&nbsp;David S Smith","doi":"10.1155/2017/7835749","DOIUrl":"https://doi.org/10.1155/2017/7835749","url":null,"abstract":"<p><strong>Purpose: </strong>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 <i>k</i>-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.</p><p><strong>Methods: </strong>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 <sub><i>α</i></sub><sup>2</sup>), 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 <i>K</i><sup>trans</sup> (volume transfer constant) and <i>v</i><sub><i>e</i></sub> (extravascular-extracellular volume fraction) across a population of random sampling schemes.</p><p><strong>Results: </strong>NN produced the lowest image error (SER: 29.1), while TV/TGV <sub><i>α</i></sub><sup>2</sup> produced the most accurate <i>K</i><sup>trans</sup> (CCC: 0.974/0.974) and <i>v</i><sub><i>e</i></sub> (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate <i>K</i><sup>trans</sup> (CCC: 0.842) and <i>v</i><sub>e</sub> (CCC: 0.799).</p><p><strong>Conclusion: </strong>TV/TGV <sub><i>α</i></sub><sup>2</sup> should be used as temporal constraints for CS DCE-MRI of the breast.</p>","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,&nbsp;Gao Wei,&nbsp;Song Zongxi","doi":"10.1155/2017/3020461","DOIUrl":"https://doi.org/10.1155/2017/3020461","url":null,"abstract":"<p><p>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.</p>","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
{"title":"A Novel Histogram Region Merging Based Multithreshold Segmentation Algorithm for MR Brain Images.","authors":"Siyan Liu,&nbsp;Xuanjing Shen,&nbsp;Yuncong Feng,&nbsp;Haipeng Chen","doi":"10.1155/2017/9759414","DOIUrl":"https://doi.org/10.1155/2017/9759414","url":null,"abstract":"<p><p>Multithreshold segmentation algorithm is time-consuming, and the time complexity will increase exponentially with the increase of thresholds. In order to reduce the time complexity, a novel multithreshold segmentation algorithm is proposed in this paper. First, all gray levels are used as thresholds, so the histogram of the original image is divided into 256 small regions, and each region corresponds to one gray level. Then, two adjacent regions are merged in each iteration by a new designed scheme, and a threshold is removed each time. To improve the accuracy of the merger operation, variance and probability are used as energy. No matter how many the thresholds are, the time complexity of the algorithm is stable at <i>O</i>(<i>L</i>). Finally, the experiment is conducted on many MR brain images to verify the performance of the proposed algorithm. Experiment results show that our method can reduce the running time effectively and obtain segmentation results with high accuracy.</p>","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/10.1155/2017/9759414","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34912736","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: 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,&nbsp;Sami Alodhayb,&nbsp;Kaamran Raahemifar,&nbsp;Vasudevan Lakshminarayanan","doi":"10.1155/2017/4826385","DOIUrl":"https://doi.org/10.1155/2017/4826385","url":null,"abstract":"<p><p>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.</p>","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,&nbsp;Hongjian Li,&nbsp;Liang Lv,&nbsp;Yufeng Zhang","doi":"10.1155/2017/9083916","DOIUrl":"https://doi.org/10.1155/2017/9083916","url":null,"abstract":"<p><strong>Objective: </strong>To develop a computer-aided method that reduces the variability of Cobb angle measurement for scoliosis assessment.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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°.</p><p><strong>Conclusion: </strong>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.</p><p><strong>Significance: </strong>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.</p>","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,&nbsp;Peng He,&nbsp;Luzhen Deng,&nbsp;Mianyi Chen,&nbsp;Biao Wei","doi":"10.1155/2017/7916260","DOIUrl":"https://doi.org/10.1155/2017/7916260","url":null,"abstract":"<p><p>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 (<i>A</i> and <i>B</i>) filled with PMMA are used to simulate imaging process through GEANT 4. Phantom <i>A</i> 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 <i>B</i> 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 <i>A</i> and <i>B</i> 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.</p>","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":"<p><p>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.</p>","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
Space and Time Resolved Detection of Platelet Activation and von Willebrand Factor Conformational Changes in Deep Suspensions. 深悬液中血小板活化和血管性血友病因子构象变化的时空分辨检测。
IF 7.6
International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-11-06 DOI: 10.1155/2017/8318906
Jacopo Biasetti, Kaushik Sampath, Angel Cortez, Alaleh Azhir, Assaf A Gilad, Thomas S Kickler, Tobias Obser, Zaverio M Ruggeri, Joseph Katz
{"title":"Space and Time Resolved Detection of Platelet Activation and von Willebrand Factor Conformational Changes in Deep Suspensions.","authors":"Jacopo Biasetti,&nbsp;Kaushik Sampath,&nbsp;Angel Cortez,&nbsp;Alaleh Azhir,&nbsp;Assaf A Gilad,&nbsp;Thomas S Kickler,&nbsp;Tobias Obser,&nbsp;Zaverio M Ruggeri,&nbsp;Joseph Katz","doi":"10.1155/2017/8318906","DOIUrl":"https://doi.org/10.1155/2017/8318906","url":null,"abstract":"<p><p>Tracking cells and proteins' phenotypic changes in deep suspensions is critical for the direct imaging of blood-related phenomena in <i>in vitro</i> replica of cardiovascular systems and blood-handling devices. This paper introduces fluorescence imaging techniques for space and time resolved detection of platelet activation, von Willebrand factor (VWF) conformational changes, and VWF-platelet interaction in deep suspensions. Labeled VWF, platelets, and VWF-platelet strands are suspended in deep cuvettes, illuminated, and imaged with a high-sensitivity EM-CCD camera, allowing detection using an exposure time of 1 ms. In-house postprocessing algorithms identify and track the moving signals. Recombinant VWF-eGFP (rVWF-eGFP) and VWF labeled with an FITC-conjugated polyclonal antibody are employed. Anti-P-Selectin FITC-conjugated antibodies and the calcium-sensitive probe Indo-1 are used to detect activated platelets. A positive correlation between the mean number of platelets detected per image and the percentage of activated platelets determined through flow cytometry is obtained, validating the technique. An increase in the number of rVWF-eGFP signals upon exposure to shear stress demonstrates the technique's ability to detect breakup of self-aggregates. VWF globular and unfolded conformations and self-aggregation are also observed. The ability to track the size and shape of VWF-platelet strands in space and time provides means to detect pro- and antithrombotic processes.</p>","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/10.1155/2017/8318906","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35650754","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
Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images. 光学结肠镜图像中多尺度目标的图像检索方法。
IF 7.6
International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-02-01 DOI: 10.1155/2017/7089213
Hirokazu Nosato, Hidenori Sakanashi, Eiichi Takahashi, Masahiro Murakawa, Hiroshi Aoki, Ken Takeuchi, Yasuo Suzuki
{"title":"Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images.","authors":"Hirokazu Nosato,&nbsp;Hidenori Sakanashi,&nbsp;Eiichi Takahashi,&nbsp;Masahiro Murakawa,&nbsp;Hiroshi Aoki,&nbsp;Ken Takeuchi,&nbsp;Yasuo Suzuki","doi":"10.1155/2017/7089213","DOIUrl":"https://doi.org/10.1155/2017/7089213","url":null,"abstract":"<p><p>Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases, such as ulcerative colitis. Thus, to assist the UC diagnosis, it is necessary to develop a new technology that can retrieve similar cases of diagnostic target image from cases in the past that stored the diagnosed images with various symptoms of colonic mucosa. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects. The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects. Through three experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any visible size and any location at a high level of accuracy.</p>","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/10.1155/2017/7089213","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34778449","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
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