J. Choi, K. Cleary, J. Zeng, K. Gary, M. Freedman, V. Watson, D. Lindisch, S. Mun
{"title":"I-SPINE: a software package for advances in image-guided and minimally invasive spine procedures","authors":"J. Choi, K. Cleary, J. Zeng, K. Gary, M. Freedman, V. Watson, D. Lindisch, S. Mun","doi":"10.1117/12.384879","DOIUrl":"https://doi.org/10.1117/12.384879","url":null,"abstract":"While image guidance is now routinely used in the brain in the form of frameless stereotaxy, it is beginning to be more widely used in other clinical areas such as the spine. At Georgetown University Medical Center, we are developing a program to provide advanced visualization and image guidance for minimally invasive spine procedures. This is a collaboration between an engineering-based research group and physicians from the radiology, neurosurgery, and orthopaedics departments. A major component of this work is the ISIS Center Spine Procedures Imaging and Navigation Engine, which is a software package under development as the base platform for technical advances.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127175325","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}
Arthur W. Wetzel, J. Gilbertson, Lei Zheng, John Gilespie, J. Swalwell, Y. Yagi, Sujin Kim, M. Emmert-Buck, M. Becich
{"title":"Three-dimensional reconstruction for genomic analysis of prostate cancer","authors":"Arthur W. Wetzel, J. Gilbertson, Lei Zheng, John Gilespie, J. Swalwell, Y. Yagi, Sujin Kim, M. Emmert-Buck, M. Becich","doi":"10.1117/12.384875","DOIUrl":"https://doi.org/10.1117/12.384875","url":null,"abstract":"Prostate cancer is the second most common cause of cancer deaths and is the most frequently detected form of cancer of males in the US. Death rate scan be greatly reduced by early treatment. Consequently, it is important to understand the cause and progression of this disease in order to improve detection and treatment methods. As part of the Cancer Genome Anatomy Project work is underway to produce a 'molecular finger print' of prostate cancer.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123710546","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}
{"title":"Task-based color scale design","authors":"P. Rheingans","doi":"10.1117/12.384882","DOIUrl":"https://doi.org/10.1117/12.384882","url":null,"abstract":"Color is commonly used in data visualization in order to convey a wide variety of types of information: metric values, pattern, extrema, emphasis, and others. A distressingly large percentage of these visualizations appear to use the default color scale for the visualization package used to create them. While sometimes this is an appropriate choice, careful consideration of the implications of color scale selection can often result in a more effective visualization. Factors which should be considered include the characteristics of the data, the questions of interest about the data, and the expected viewers of the representation.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131732688","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}
{"title":"Panoramic-image-based rendering solutions for visualizing remote locations via the web","authors":"U. Obeysekare, David Egts, J. Bethmann","doi":"10.1117/12.384884","DOIUrl":"https://doi.org/10.1117/12.384884","url":null,"abstract":"With advances in panoramic image-based rendering techniques and the rapid expansion of web advertising, new techniques are emerging for visualizing remote locations on the WWW. Success of these techniques depends on how easy and inexpensive it is to develop a new type of web content that provides pseudo 3D visualization at home, 24-hours a day. Furthermore, the acceptance of this new visualization medium depends on the effectiveness of the familiarization tools by a segment of the population that was never exposed to this type of visualization. This paper addresses various hardware and software solutions available to collect, produce, and view panoramic content. While cost and effectiveness of building the content is being addressed using a few commercial hardware solutions, effectiveness of familiarization tools is evaluated using a few sample data sets.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125594740","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}
{"title":"Performance characterization of vision algorithms","authors":"R. Haralick, Visvanathan Ramesh","doi":"10.1117/12.47987","DOIUrl":"https://doi.org/10.1117/12.47987","url":null,"abstract":"In order to design vision systems which work, a sound engineering methodology must be utilized. In the systems engineering approach, a complex system is divided into simple subsystems and from the input/output characteristics of each subsystem, the input/output characteristics of the total system can be determined. Machine vision systems are complex, and they are composed of different algorithms applied in sequence. Determination of the performance of a total machine vision system is possible if the performance of each of the subpieces, i.e. the algorithms, is given. The problem, however, is that for most algorithms, there is no performance characterization which has been established and published in the research literature. Performance characterization has to do with establishing the correspondence of the random variations and imperfections which the algorithm produces on the output data caused by the random variations and imperfections of the input data. This paper illustrates how random perturbation models and propagation of random errors can be set up for a vision algorithm involving edge detection, edge linking, arc segmentation, and line fitting. The paper also discusses important dimensions that must be included in the performance characterization of any vision module performing a parametric estimation such as object pose, curve fit, or edge orientation estimation. Finally, we outline a general parametric model having three components: a relational model; a noise model; and a computational estimation model.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126559880","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}
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