2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)最新文献

Scale-Less Feature-Spatial Matching 无尺度特征-空间匹配

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691526

Chao Zhang, Tingzhi Shen

引用次数: 0

Automated Classification of Bone and Air Volumes for Hybrid PET-MRI Brain Imaging 混合PET-MRI脑成像中骨和空气体积的自动分类

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691483

S. Chan, R. Jeffree, M. Fay, S. Crozier, Zhengyi Yang, Y. Gal, P. Thomas

{"title":"Automated Classification of Bone and Air Volumes for Hybrid PET-MRI Brain Imaging","authors":"S. Chan, R. Jeffree, M. Fay, S. Crozier, Zhengyi Yang, Y. Gal, P. Thomas","doi":"10.1109/DICTA.2013.6691483","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691483","url":null,"abstract":"In clinically applicable structural magnetic resonance images (MRI), bone and air have similarly low signal intensity, making the differentiation between them a very challenging task. MRI-based bone/air segmentation, however, is a critical step in some emerging applications, such as skull atlas building, MRI-based attenuation correction for Positron Emission Tomography (PET), and MRI-based radiotherapy planning. In view of the availability of hybrid PET-MRI machines, we propose a voxel-wise classification method for bone/air segmentation. The method is based on random forest theory and features extracted from structural MRI and attenuation uncorrected PET. The Dice Similarity Score (DSC) score between the segmentation result and the 'ground truth' obtained by thresholding Computed Tomography images was calculated for validation. Images from 10 subjects were used for validation, achieving a DSC of 0.83±0.08 and 0.98±0.01 for air and bone, respectively. The results suggest that structural MRI and uncorrected PET can be used to reliably differentiate between air and bone.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127516236","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: 14

Robust 3D Multi-Modal Registration of MRI Volumes Using the Sum of Conditional Variance 基于条件方差和的MRI体积鲁棒三维多模态配准

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691520

Mst. Nargis Aktar, M. Alam, A. Lambert, M. Pickering

引用次数: 2

Automated Segmentation of Prostate MR Images Using Prior Knowledge Enhanced Random Walker 基于先验知识增强随机漫步器的前列腺磁共振图像自动分割

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691485

Ang Li, Changyang Li, Xiuying Wang, S. Eberl, D. Feng, M. Fulham

{"title":"Automated Segmentation of Prostate MR Images Using Prior Knowledge Enhanced Random Walker","authors":"Ang Li, Changyang Li, Xiuying Wang, S. Eberl, D. Feng, M. Fulham","doi":"10.1109/DICTA.2013.6691485","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691485","url":null,"abstract":"Prostate cancer is the second most common cause of cancer deaths in males. Accurate prostate segmentation from magnetic resonance (MR) images is critical to the diagnosis and treatment of prostate cancer. Automated prostate segmentation is challenging due to the variety in shapes and sizes of the prostate. Furthermore, the expected boundaries of ROIs are often indistinct, while heterogeneity concurrently exists within the ROIs. To address these challenges, we propose an automated approach that incorporates the local intensity features by random walker (RW) algorithm and global probability knowledge from an atlas to better describe unique characteristics of the prostate in MR images. We formulated a new RW weight function to take into account atlas probabilities and intensity differences. The prior knowledge from the atlas probability map not only reflects the statistical shape approximation of the prostate but also provides confinement and guidance for RW segmentation. Our approach was validated and compared with the conventional RW algorithm on segmenting 30 3-T prostate MR volumes. The experimental results indicated that our approach with an average DSC of 80.7±5.1%, outperformed that of the conventional RW (average DSC = 71.9±9.1%) and several other reported methods in terms of DSC accuracy and robustness.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133417637","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: 16

Predicting Shot Locations in Tennis Using Spatiotemporal Data 利用时空数据预测网球击球位置

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691516

Xinyu Wei, P. Lucey, S. Morgan, S. Sridharan

{"title":"Predicting Shot Locations in Tennis Using Spatiotemporal Data","authors":"Xinyu Wei, P. Lucey, S. Morgan, S. Sridharan","doi":"10.1109/DICTA.2013.6691516","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691516","url":null,"abstract":"Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114706752","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: 32

Learning Discriminative Local Patterns with Unrestricted Structure for Face Recognition 基于非限制结构的判别局部模式学习

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691504

Douglas Brown, Yongsheng Gao, J. Zhou

引用次数: 0

A Novel Representation of Bioacoustic Events for Content-Based Search in Field Audio Data 基于内容的现场音频数据搜索中生物声事件的一种新表示

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691473

Xueyan Dong, M. Towsey, Jinglan Zhang, Jasmine Banks, P. Roe

引用次数: 18

Ad Hoc Radiometric Calibration of a Thermal-Infrared Camera 热红外相机的特别辐射定标

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691478

Stephen Vidas, Peyman Moghadam

引用次数: 7

Pose Priors for Aerial Image Registration 姿态先验的航空图像注册

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691515

A. Marburg, M. Hayes, A. Bainbridge-Smith

引用次数: 6

Automated Selection of Optimal Frames in NIR Iris Videos 在近红外虹膜视频中自动选择最佳帧

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691486

Nitin K. Mahadeo, A. Paplinski, S. Ray

{"title":"Automated Selection of Optimal Frames in NIR Iris Videos","authors":"Nitin K. Mahadeo, A. Paplinski, S. Ray","doi":"10.1109/DICTA.2013.6691486","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691486","url":null,"abstract":"A relatively new trend in the iris biometric area is the use of videos as a capturing device. Frame by frame approach is richer in information and gives more flexibility as opposed to the use of traditional still images. However, the quality, shape and size of the iris may vary from one frame to another. In this paper, we propose a new technique for selecting the best frames in an iris video. Taking advantage of the temporal correspondence in iris frames, we classify iris videos into 3 categories, namely Adequate, Motion Constrained and Time Constrained. Frames with blinks and off-angle gaze are eliminated using frame averaging and correlation. Quality factors, namely motion blur, out of focus, translational motion and lighting present in iris videos are detected and their effect on recognition performance is investigated. Experimental results are carried out on both the MBGC NIR Iris Video and the MBGC NIR Iris Still datasets from the National Institute for Standards and Technology (NIST). Firstly, this work demonstrates that the proposed optimal frame selection technique in NIR Iris Videos leads to significant improvement in recognition performance. Secondly, the performance of NIR Iris Still images vs. NIR Iris Videos is compared. Thirdly, we show that interoperability between iris frames and iris images in an iris recognition system affects performance. Finally, the computational time and the elimination of noisy frames at each stage using the proposed method are examined.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130023529","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: 8