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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 L Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CAIP  
  Notes IAM; ADAS Approved no  
  Call Number (down) IAM @ iam @ HGR2011 Serial 1676  
Permanent link to this record
 

 
Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva edit   pdf
openurl 
  Title On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging Type Conference Article
  Year 2005 Publication Proceeding of the 2005 conference on Artificial Intelligence Research and Development Abbreviated Journal  
  Volume Issue Pages 67-74  
  Keywords classification; vessel border modelling; IVUS  
  Abstract IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Amsterdam, The Netherlands Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number (down) IAM @ iam @ HGR2005c Serial 1549  
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias edit   pdf
doi  openurl
  Title Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images Type Conference Article
  Year 2004 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 31 Issue Pages 229-232  
  Keywords  
  Abstract The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Chicago (USA) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; MILAB Approved no  
  Call Number (down) IAM @ iam @ HGR2004 Serial 1555  
Permanent link to this record
 

 
Author Aura Hernandez-Sabate; Debora Gil; Josefina Mauri; Petia Radeva edit   pdf
openurl 
  Title Reducing cardiac motion in IVUS sequences Type Conference Article
  Year 2006 Publication Proceeding of Computers in Cardiology Abbreviated Journal  
  Volume 33 Issue Pages 685-688  
  Keywords  
  Abstract Cardiac vessel displacement is a main artifact in IVUS sequences. It hinders visualization of the main structures in an appropriate orientation and alignment and affects extracting vessel measurements. In this paper, we present a novel approach for image sequence alignment based on spectral analysis, which removes rigid dynamics, preserving at the same time the vessel geometry. First, we suppress the translation by taking, for each frame, the center of mass of the image as origin of coordinates. In polar coordinates with such point as origin, the rotation appears as a horizontal displacement. The translation induces a phase shift in the Fourier coefficients of two consecutive polar images. We estimate the phase by adjusting a regression plane to the phases of the principal frequencies. Experiments show that the presented strategy suppress cardiac motion regardless of the acquisition device. 1.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; MILAB Approved no  
  Call Number (down) IAM @ iam @ HGM2006a Serial 1554  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva; Fernando Vilariño edit   pdf
isbn  openurl
  Title Anisotropic Contour Completion Type Conference Article
  Year 2003 Publication Proceedings of the IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic structural element that takes into account the local orientation of the contours to be closed. Experiments on contours extracted from real images show that ACC produces shapes able to adapt to any curve in an active contour framework. 1.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Barcelona, Spain Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-7803-7751-6 Medium  
  Area Expedition Conference  
  Notes IAM;MV;MILAB;SIAI Approved no  
  Call Number (down) IAM @ iam @ GRV2003 Serial 1539  
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Author Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri edit   pdf
url  openurl
  Title Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach Type Conference Article
  Year 2000 Publication International Conference on Pattern Recognition Abbreviated Journal  
  Volume 4 Issue Pages 352-355  
  Keywords  
  Abstract Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number (down) IAM @ iam @ GRS2000a Serial 1537  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri edit   pdf
openurl 
  Title Automatic Segmentation of Artery Wall in Coronary IVUS Images: a Probabilistic Approach Type Conference Article
  Year 2000 Publication Proceedings of CIC’2000 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Cambridge, Massachussets Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CIC  
  Notes IAM;MILAB Approved no  
  Call Number (down) IAM @ iam @ GRS2000 Serial 1538  
Permanent link to this record
 

 
Author Debora Gil; Oriol Rodriguez; Josepa Mauri; Petia Radeva edit  openurl
  Title Statistical descriptors of the Myocardial perfusion in angiographic images Type Conference Article
  Year 2006 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume Issue Pages 677-680  
  Keywords Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification.  
  Abstract Restoration of coronary flow after primary percutaneous coronary intervention in acute myocardial infarction does not always correlate with adequate myocardial perfusion. Recently, coronary angiography has been used to assess microcirculation integrity (Myocardial BlushAnalysis, MBA). Although MBA correlates with patient prognosis there are few image processing methods addressing objective perfusion quantification. The goal of this work is to develop statistical descriptors of the myocardial dyeing pattern allowing objective assessment of myocardial perfusion. Experiments on healthy right coronary arteries show that our approach allows reliable measurements without any specific image acquisition protocol.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number (down) IAM @ iam @ GRR2006 Serial 1528  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva; Josefina Mauri edit   pdf
openurl 
  Title Ivus Segmentation Via a Regularized Curvature Flow Type Conference Article
  Year 2002 Publication X Congreso Anual de la Sociedad Española de Ingeniería Biomédica CASEIB 2002 Abbreviated Journal  
  Volume Issue Pages 133-136  
  Keywords  
  Abstract Cardiac diseases are diagnosed and treated through a study of the morphology and dynamics of cardiac arteries. In- travascular Ultrasound (IVUS) imaging is of high interest to physicians since it provides both information. At the current state-of-the-art in image segmentation, a robust detection of the arterial lumen in IVUS demands manual intervention or ECG-gating. Manual intervention is a tedious and time consuming task that requires experienced observers, meanwhile ECG-gating is an acquisition technique not available in all clinical centers. We introduce a parametric algorithm that detects the arterial luminal border in in vivo sequences. The method consist in smoothing the sequences’ level surfaces under a regularized mean curvature flow that admits non-trivial steady states. The flow is based on a measure of the surface local smoothness that takes into account regularity of the surface curvature.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Saragossa, Espanya Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number (down) IAM @ iam @ GRM2002 Serial 1536  
Permanent link to this record
 

 
Author Jaume Garcia; David Rotger; Francesc Carreras; R.Leta; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title Contrast echography segmentation and tracking by trained deformable models Type Conference Article
  Year 2003 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 30 Issue Pages 173-176  
  Keywords  
  Abstract The objective of this work is to segment the human left ventricle myocardium (LVM) in contrast echocardiography imaging and thus track it along a cardiac cycle in order to extract quantitative data about heart function. Ultrasound images are hard to work with due to their speckle appearance. To overcome this we report the combination of active contour models (ACM) or snakes and active shape models (ASM). The ability of ACM in giving closed and smooth curves in addition to the power of the ASM in producing shapes similar to the ones learned, evoke to a robust algorithm. Meanwhile the snake is attracted towards image main features, ASM acts as a correction factor. The algorithm was tested independently on 180 frames and satisfying results were obtained: in 95% the maximum difference between automatic and experts segmentation was less than 12 pixels.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Centre de Visió per Computador – Dept. Informàtica, UAB Edifici O – Campus UAB, 08193 Bellater Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0276-6547 ISBN 0-7803-8170-X Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number (down) IAM @ iam @ GRC2003 Serial 1512  
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