2018 Digital Image Computing: Techniques and Applications (DICTA)最新文献_第10页

Active Contours Based on An Anisotropic Diffusion 基于各向异性扩散的活动轮廓

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615767

Shafiullah Soomro, K. Choi

{"title":"Active Contours Based on An Anisotropic Diffusion","authors":"Shafiullah Soomro, K. Choi","doi":"10.1109/DICTA.2018.8615767","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615767","url":null,"abstract":"Image Segmentation is one of the pivotal procedure in the field of imaging and its objective is to catch required boundaries inside an image. In this paper, we propose a novel active contour method based on anisotropic diffusion. Global regionbased active contour methods rely on global intensity information across the regions. However, these methods fail to produce desired segmentation results when an image has some background variations or noise. In this regard, we adapt Perona and Malik smoothing technique as enhancement step. This technique provides interregional smoothing, sharpens the boundaries and blurs the background of an image. Our main role is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. Minimizing an energy function using partial differential framework produce results with semantically meaningful boundaries instead of capturing impassive regions. Finally, we use Gaussian kernel to eliminate problem of reinitialization in level set function. We use images taken from different modalities to validate the outcome of the proposed method. In the result section, we have evaluated that, the proposed method achieves good results qualitatively and quantitatively with high accuracy compared to other state-of-the-art models.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132544227","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

A Scale-Free and Parameter-Free Image Edge Strength Measure 一种无尺度、无参数的图像边缘强度测量方法

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615813

Guy Smith, P. Jackway

引用次数: 0

Inter-Subject Image Registration of Clinical Neck MRI Volumes using Discrete Periodic Spline Wavelet and Free form Deformation 基于离散周期样条小波和自由变形的临床颈部MRI体间图像配准

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615825

A. Suman, Md. Asikuzzaman, A. Webb, D. Perriman, M. Pickering

{"title":"Inter-Subject Image Registration of Clinical Neck MRI Volumes using Discrete Periodic Spline Wavelet and Free form Deformation","authors":"A. Suman, Md. Asikuzzaman, A. Webb, D. Perriman, M. Pickering","doi":"10.1109/DICTA.2018.8615825","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615825","url":null,"abstract":"This paper presents a framework for inter-patient image registration which uses a multi-thresholds, multi-similarity measures and multi-transformations based on compactly supported spline and discrete periodic spline wavelets (DPSWs) using the Gauss-Newton gradient descent (GNGD) and gradient descent (GD) optimization methods. Our primary intellectual contribution is incorporating DPSWs in the transformation while another includes fusing out-of-range concept in a surface matching technique which is implemented by a multi-transformations and multi-similarity measures. In particular, as a true deformation cannot be achieved by single combination of transformation, similarity measure (SM) and optimization of a registration process, a moving image is required to be brought within the range of a registration. On the other hand, the surface matching technique involves an edge position difference (EPD) SM in which coarse to fine surfaces are matched using multiple thresholds with a spline-based free from deformation (FFD) method. The registration experiments were performed on 3D clinical neck magnetic resonance (MR) images, with the results showing that our proposed method provides good accuracy and robustness.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132998156","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: 3

Railway Infrastructure Defects Recognition using Fine-grained Deep Convolutional Neural Networks 基于细粒度深度卷积神经网络的铁路基础设施缺陷识别

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615868

Huaxi Huang, Jingsong Xu, Jian Zhang, Qiang Wu, Christina Kirsch

引用次数: 7

Information Enhancement for Travelogues via a Hybrid Clustering Model 基于混合聚类模型的游记信息增强

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615849

Lu Zhang, Jingsong Xu, Jian Zhang, Yongshun Gong

{"title":"Information Enhancement for Travelogues via a Hybrid Clustering Model","authors":"Lu Zhang, Jingsong Xu, Jian Zhang, Yongshun Gong","doi":"10.1109/DICTA.2018.8615849","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615849","url":null,"abstract":"Travelogues consist of textual information shared by tourists through web forums or other social media which often lack illustrations (images). In image sharing websites like Flicker, users can post images with rich textual information: ‘title’, ‘tag’ and ‘description’. The topics of travelogues usually revolve around beautiful sceneries. Corresponding landscape images recommended to these travelogues can enhance the vividness of reading. However, it is difficult to fuse such information because the text attached to each image has diverse meanings/views. In this paper, we propose an unsupervised Hybrid Multiple Kernel K-means (HMKKM) model to link images and travelogues through multiple views. Multi-view matrices are built to reveal the correlations between several respects. For further improving the performance, we add a regularisation based on textual similarity. To evaluate the effectiveness of the proposed method, a dataset is constructed from TripAdvisor and Flicker to find the related images for each travelogue. Experiment results demonstrate the superiority of the proposed model by comparison with other baselines.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130223627","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

Bone Age Assessment Based on Two-Stage Deep Neural Networks 基于两阶段深度神经网络的骨龄评估

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615764

Meicheng Chu, Bo Liu, F. Zhou, X. Bai, Bin Guo

引用次数: 12

Band Weighting Network for Hyperspectral Image Classification 高光谱图像分类的波段加权网络

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615876

Jing Wang, Jun Zhou

引用次数: 7

Impact of MRI Protocols on Alzheimer's Disease Detection MRI方案对阿尔茨海默病检测的影响

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615774

Saruar Alam, Len Hamey, K. Ho-Shon

{"title":"Impact of MRI Protocols on Alzheimer's Disease Detection","authors":"Saruar Alam, Len Hamey, K. Ho-Shon","doi":"10.1109/DICTA.2018.8615774","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615774","url":null,"abstract":"Alzheimer's disease (AD) can be detected using magnetic resonance imaging (MRI) based features and supervised classifiers. The subcortical and ventricular volumes change for AD patients. These volumes can be extracted from MRI by tools such as FreeSurfer and the multi-atlas-based likelihood fusion (MALF) algorithm. Studies use MRI from many medical imaging centers. However, individual centers typically use distinctive MRI protocols for brain scanning. The protocol differences include different scanner models with various operating parameters. Some scanner models have different field strengths. A key factor in classifying multicentric MR subject images having different protocols is how different scanner models affect the extraction of feature, and the subsequent classification performance of a supervised classifier. We have investigated the classification performance of FreeSurfer and MALF based volume features together with Radial Basis Function Support Vector Machine and Extreme Learning Machine across different imaging protocols. We have also investigated for both FreeSurfer and MALF, which brain regions are most effective for the detection of the disease under different protocols. Our study result indicates marginal differences in classification performance across scanner models with the same or different field strengths when differentiating AD, Mild Cognitive Impairment, and Normal Controls. We have also observed differences in ranking order of the most effective brain regions.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114705779","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

Fast and Energy-Efficient Time-of-Flight Distance Sensing Method for 3D Object Tracking 一种快速节能的三维目标跟踪飞行时间距离传感方法

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615790

H. Plank, G. Holweg, C. Steger, N. Druml

引用次数: 0

Memory Optimized Deep Dense Network for Image Super-resolution 内存优化深度密集网络图像超分辨率

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615829

Jialiang Shen, Yucheng Wang, Jian Zhang

引用次数: 0