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Author Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie edit   pdf
url  openurl
  Title Inferring the Performance of Medical Imaging Algorithms Type Conference Article
  Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 6854 Issue Pages 520-528  
  Keywords Validation, Statistical Inference, Medical Imaging Algorithms.  
  Abstract Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.
 
  Address Sevilla  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Berlin Editor Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch  
  Language Summary Language Original Title  
  Series Editor Series Title (up) L Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CAIP  
  Notes IAM; ADAS Approved no  
  Call Number IAM @ iam @ HGR2011 Serial 1676  
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Author Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate edit   pdf
doi  isbn
openurl 
  Title Error Analysis for Lucas-Kanade Based Schemes Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 184-191  
  Keywords Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance  
  Abstract Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.  
  Address Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor  
  Language english Summary Language Original Title  
  Series Editor Campilho, Aurélio and Kamel, Mohamed Series Title (up) Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium  
  Area Expedition Conference ICIAR  
  Notes IAM Approved no  
  Call Number IAM @ iam @ MGH2012a Serial 1899  
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