Visual Computing for Industry, Biomedicine, and Art最新文献_第8页

Review of heterogeneous material objects modeling in additive manufacturing. 增材制造中的异质材料物体建模综述。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-03-05 DOI: 10.1186/s42492-020-0041-6

Bin Li, Jianzhong Fu, Jiawei Feng, Ce Shang, Zhiwei Lin

引用次数: 0

Analytic time-of-flight positron emission tomography reconstruction: three-dimensional case. 解析飞行时间正电子发射层析成像重建:三维案例。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-02-17 DOI: 10.1186/s42492-020-0042-5

Gengsheng L Zeng, Ya Li, Qiu Huang

引用次数: 1

Hybrid image of three contents. 三种内容的混合图像。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-02-10 DOI: 10.1186/s42492-019-0036-3

Peeraya Sripian, Yasushi Yamaguchi

{"title":"Hybrid image of three contents.","authors":"Peeraya Sripian, Yasushi Yamaguchi","doi":"10.1186/s42492-019-0036-3","DOIUrl":"https://doi.org/10.1186/s42492-019-0036-3","url":null,"abstract":"A hybrid image allows multiple image interpretations to be modulated by the viewing distance. Originally, it can be constructed by combining the low and high spatial frequencies of two different images. The original hybrid image synthesis was limited to similar shapes of source images that were aligned in the edges, e.g., faces with a different expression, to produce an effective double image interpretation. In our previous work, we proposed a noise-inserted method for synthesizing a hybrid image from dissimilar shape images or unaligned images. In this work, we propose a novel method for adding an image to be seen from a middle viewing distance. The middle-frequency (MF) image is extracted by a special bandpass filter, which generates ringing while extracting only specified frequency bands. With this method, the middle frequency should be perceived as a meaningless pattern when viewed from a far distance and close up. A parameter tuning experiment was performed to determine the suitable cutoff frequencies for designing the filter for the MF image. We found that ringings of a suitable size could be used to make the middle frequency less noticeable when seen from far away.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"3 1","pages":"4"},"PeriodicalIF":0.0,"publicationDate":"2020-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0036-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Painting image browser applying an associate-rule-aware multidimensional data visualization technique. 应用关联规则感知多维数据可视化技术的绘图图像浏览器。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-02-05 DOI: 10.1186/s42492-019-0040-7

Ayaka Kaneko, Akiko Komatsu, Takayuki Itoh, Florence Ying Wang

{"title":"Painting image browser applying an associate-rule-aware multidimensional data visualization technique.","authors":"Ayaka Kaneko, Akiko Komatsu, Takayuki Itoh, Florence Ying Wang","doi":"10.1186/s42492-019-0040-7","DOIUrl":"https://doi.org/10.1186/s42492-019-0040-7","url":null,"abstract":"Exploration of artworks is enjoyable but often time consuming. For example, it is not always easy to discover the favorite types of unknown painting works. It is not also always easy to explore unpopular painting works which looks similar to painting works created by famous artists. This paper presents a painting image browser which assists the explorative discovery of user-interested painting works. The presented browser applies a new multidimensional data visualization technique that highlights particular ranges of particular numeric values based on association rules to suggest cues to find favorite painting images. This study assumes a large number of painting images are provided where categorical information (e.g., names of artists, created year) is assigned to the images. The presented system firstly calculates the feature values of the images as a preprocessing step. Then the browser visualizes the multidimensional feature values as a heatmap and highlights association rules discovered from the relationships between the feature values and categorical information. This mechanism enables users to explore favorite painting images or painting images that look similar to famous painting works. Our case study and user evaluation demonstrates the effectiveness of the presented image browser.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"3 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2020-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Research on a bifurcation location algorithm of a drainage tube based on 3D medical images. 基于三维医学图像的引流管分岔定位算法研究。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-01-14 DOI: 10.1186/s42492-019-0039-0

Qiuling Pan, Wei Zhu, Xiaolin Zhang, Jincai Chang, Jianzhong Cui

引用次数: 4

Novel indoor positioning system based on ultra-wide bandwidth. 基于超宽带的新型室内定位系统。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2020-01-07 DOI: 10.1186/s42492-019-0038-1

Zhen Wei, Rui Jiang, Xing Wei, Yun-An Cheng, Lei Cheng, Cai Wang

引用次数: 7

Multi-scale characterizations of colon polyps via computed tomographic colonography. 通过计算机断层结肠镜检查结肠息肉的多尺度特征。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2019-12-27 DOI: 10.1186/s42492-019-0032-7

Weiguo Cao, Marc J Pomeroy, Yongfeng Gao, Matthew A Barish, Almas F Abbasi, Perry J Pickhardt, Zhengrong Liang

{"title":"Multi-scale characterizations of colon polyps via computed tomographic colonography.","authors":"Weiguo Cao, Marc J Pomeroy, Yongfeng Gao, Matthew A Barish, Almas F Abbasi, Perry J Pickhardt, Zhengrong Liang","doi":"10.1186/s42492-019-0032-7","DOIUrl":"https://doi.org/10.1186/s42492-019-0032-7","url":null,"abstract":"Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"2 1","pages":"25"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0032-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Facial expression recognition using three-stage support vector machines. 基于三级支持向量机的面部表情识别。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2019-12-16 DOI: 10.1186/s42492-019-0034-5

Issam Dagher, Elio Dahdah, Morshed Al Shakik

{"title":"Facial expression recognition using three-stage support vector machines.","authors":"Issam Dagher, Elio Dahdah, Morshed Al Shakik","doi":"10.1186/s42492-019-0034-5","DOIUrl":"https://doi.org/10.1186/s42492-019-0034-5","url":null,"abstract":"Herein, a three-stage support vector machine (SVM) for facial expression recognition is proposed. The first stage comprises 21 SVMs, which are all the binary combinations of seven expressions. If one expression is dominant, then the first stage will suffice; if two are dominant, then the second stage is used; and, if three are dominant, the third stage is used. These multilevel stages help reduce the possibility of experiencing an error as much as possible. Different image preprocessing stages are used to ensure that the features attained from the face detected have a meaningful and proper contribution to the classification stage. Facial expressions are created as a result of muscle movements on the face. These subtle movements are detected by the histogram-oriented gradient feature, because it is sensitive to the shapes of objects. The features attained are then used to train the three-stage SVM. Two different validation methods were used: the leave-one-out and K-fold tests. Experimental results on three databases (Japanese Female Facial Expression, Extended Cohn-Kanade Dataset, and Radboud Faces Database) show that the proposed system is competitive and has better performance compared with other works.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"2 1","pages":"24"},"PeriodicalIF":0.0,"publicationDate":"2019-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0034-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Analytic time-of-flight positron emission tomography reconstruction: two-dimensional case. 解析飞行时间正电子发射断层成像重建:二维情况。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2019-12-09 DOI: 10.1186/s42492-019-0035-4

Gengsheng L Zeng, Ya Li, Qiu Huang

{"title":"Analytic time-of-flight positron emission tomography reconstruction: two-dimensional case.","authors":"Gengsheng L Zeng, Ya Li, Qiu Huang","doi":"10.1186/s42492-019-0035-4","DOIUrl":"https://doi.org/10.1186/s42492-019-0035-4","url":null,"abstract":"In a positron emission tomography (PET) scanner, the time-of-flight (TOF) information gives us rough event position along the line-of-response (LOR). Using the TOF information for PET image reconstruction is able to reduce image noise. The state-of-the-art TOF PET image reconstruction uses iterative algorithms. Analytical image reconstruction algorithm exits for TOF PET which emulates the iterative Landweber algorithm. This paper introduces such an algorithm, focusing on two-dimensional (2D) reconstruction. The proposed algorithm is in the form of backprojection filtering, in which the backprojection is performed first, and then a 2D filter is applied to the backprojected image. For the list-mode data, the backprojection is carried out in the event-by-event fashion, and a profile function may be used along the projection LOR. The 2D filter depends on the TOF timing resolution as well as the backprojection profile function. In order to emulate the iterative algorithm effects, a Fourier-domain window function is suggested. This window function has a parameter, k, which corresponds to the iteration number in an iterative algorithm.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"2 1","pages":"22"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42492-019-0035-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37795164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning. 利用深度学习实现光学相干断层血管造影中浅表眼窝血管缺损区的自动量化。

4区计算机科学

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2019-12-09 DOI: 10.1186/s42492-019-0031-8

Menglin Guo, Mei Zhao, Allen M Y Cheong, Houjiao Dai, Andrew K C Lam, Yongjin Zhou

{"title":"Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning.","authors":"Menglin Guo, Mei Zhao, Allen M Y Cheong, Houjiao Dai, Andrew K C Lam, Yongjin Zhou","doi":"10.1186/s42492-019-0031-8","DOIUrl":"10.1186/s42492-019-0031-8","url":null,"abstract":"An accurate segmentation and quantification of the superficial foveal avascular zone (sFAZ) is important to facilitate the diagnosis and treatment of many retinal diseases, such as diabetic retinopathy and retinal vein occlusion. We proposed a method based on deep learning for the automatic segmentation and quantification of the sFAZ in optical coherence tomography angiography (OCTA) images with robustness to brightness and contrast (B/C) variations. A dataset of 405 OCTA images from 45 participants was acquired with Zeiss Cirrus HD-OCT 5000 and the ground truth (GT) was manually segmented subsequently. A deep learning network with an encoder-decoder architecture was created to classify each pixel into an sFAZ or non-sFAZ class. Subsequently, we applied largest-connected-region extraction and hole-filling to fine-tune the automatic segmentation results. A maximum mean dice similarity coefficient (DSC) of 0.976 ± 0.011 was obtained when the automatic segmentation results were compared against the GT. The correlation coefficient between the area calculated from the automatic segmentation results and that calculated from the GT was 0.997. In all nine parameter groups with various brightness/contrast, all the DSCs of the proposed method were higher than 0.96. The proposed method achieved better performance in the sFAZ segmentation and quantification compared to two previously reported methods. In conclusion, we proposed and successfully verified an automatic sFAZ segmentation and quantification method based on deep learning with robustness to B/C variations. For clinical applications, this is an important progress in creating an automated segmentation and quantification applicable to clinical analysis.","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":"2 1","pages":"21"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37796399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0