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Author  |
Patricia Marquez |
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Title |
Conditions Ensuring Accuracy of Local Optical Flow Schemes |
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Report |
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2010 |
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CVC Tehcnical Report |
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157 |
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Accurate computation of optical flow is a key-point in many image processing fields. Detection of anomalous and unpredicted agents (such as pedestrians, bikers or cars) in urban scenes or pathology discrimination in medical imaging sequences, to mention just a two. The above kinds sequences present two main difficulties for standard optical flow techniques. On one hand, variability in acquisition conditions (illuminance, medical imaging modality, ...) force an alterantive representation for images fulfilling the britghtness constancy constrain. On the hand, current variational schemes produce oversmoothed fields unable to properly model discontinuous behaviours such as collisions or functionless pathological areas. This master project explores the abilities and limitations of local and global optical flow approaches. The master student will put especial emphasis in the theoretical grounds behind in order to design a variational framework combining the theoretical advantages of the considered techniques. In particular an optical flow based on Gabor phase tracking (developed in the group for medical imaging) will be generalized to urban scenes. |
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Master's thesis |
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Bellaterra 08193, Barcelona, Spain |
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IAM; |
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IAM @ iam @ Mar2010 |
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1582 |
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Author |
Patricia Marquez |
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Title |
A Confidence Framework for the Assessment of Optical Flow Performance |
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Year |
2015 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.
This thesis provides a framework able to decide which pairs “ optical flow – confidence measure” (OF-CM) are best suited for optical flow error bounding given a confidence level determined by a decision support system. To design this framework we cover the following points:
Descriptive scores. As a first step, we summarize and analyze the sources of inaccuracies in the output of optical flow algorithms. Second, we present several descriptive plots that visually assess CM capabilities for OF error bounding. In addition to the descriptive plots, given a plot representing OF-CM capabilities to bound the error, we provide a numeric score that categorizes the plot according to its decreasing profile, that is, a score assessing CM performance.
Statistical framework. We provide a comparison framework that assesses the best suited OF-CM pair for error bounding that uses a two stage cascade process. First of all we assess the predictive value of the confidence measures by means of a descriptive plot. Then, for a sample of descriptive plots computed over training frames, we obtain a generic curve that will be used for sequences with no ground truth. As a second step, we evaluate the obtained general curve and its capabilities to really reflect the predictive value of a confidence measure using the variability across train frames by means of ANOVA.
The presented framework has shown its potential in the application on clinical decision support systems. In particular, we have analyzed the impact of the different image artifacts such as noise and decay to the output of optical flow in a cardiac diagnose system and we have improved the navigation inside the bronchial tree on bronchoscopy. |
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July 2015 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Debora Gil;Aura Hernandez |
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978-84-943427-2-1 |
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IAM; 600.075 |
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Admin @ si @ Mar2015 |
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2687 |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
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Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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7324 |
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I |
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184-191 |
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Keywords |
Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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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. |
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Aveiro, Portugal |
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Springer-Verlag Berlin Heidelberg |
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english |
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Campilho, Aurélio and Kamel, Mohamed |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-31294-6 |
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ICIAR |
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IAM |
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Call Number |
IAM @ iam @ MGH2012a |
Serial |
1899 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
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Conference Article |
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Year |
2011 |
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IEEE International Conference on Computer Vision – Workshops |
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2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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IEEE |
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Barcelona (Spain) |
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English |
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English |
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ICCVW |
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IAM; ADAS |
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Call Number |
IAM @ iam @ MGH2011 |
Serial |
1682 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality |
Type |
Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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624-631 |
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Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field. |
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Sydney; Australia; December 2013 |
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CVTT:E2M |
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IAM; ADAS; 600.044; 600.057; 601.145 |
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no |
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Call Number |
Admin @ si @ MGH2013b |
Serial |
2351 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann |
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Title |
When Is A Confidence Measure Good Enough? |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th International Conference on Computer Vision Systems |
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7963 |
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344-353 |
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Keywords |
Optical flow, confidence measure, performance evaluation |
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Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions,
thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. |
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St Petersburg; Russia; July 2013 |
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Springer Link |
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LNCS |
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0302-9743 |
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978-3-642-39401-0 |
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ICVS |
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IAM;ADAS; 600.044; 600.057; 600.060; 601.145 |
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IAM @ iam @ MGH2013a |
Serial |
2218 |
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Author |
Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate |
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Title |
Local Analysis of Confidence Measures for Optical Flow Quality Evaluation |
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Conference Article |
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2014 |
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9th International Conference on Computer Vision Theory and Applications |
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3 |
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450-457 |
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Keywords |
Optical Flow; Confidence Measure; Performance Evaluation. |
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Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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Lisboa; January 2014 |
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VISAPP |
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IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 |
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Admin @ si @ MGM2014 |
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2432 |
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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
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Conference Article |
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2014 |
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17th International Conference on Medical Image Computing and Computer Assisted Intervention |
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8896 |
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231-238 |
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Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across di erent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three di erent OF methods, including HARP. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-14677-5 |
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STACOM |
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IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
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Admin @ si @ MKF2014 |
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2495 |
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Author |
Patricia Marquez;Debora Gil;Aura Hernandez-Sabate |
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Title |
A Complete Confidence Framework for Optical Flow |
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Conference Article |
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2012 |
Publication |
12th European Conference on Computer Vision – Workshops and Demonstrations |
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7584 |
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2 |
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124-133 |
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Optical flow, confidence measures, sparsification plots, error prediction plots |
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Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. |
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Springer-Verlag |
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Florence, Italy, October 7-13, 2012 |
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Andrea Fusiello, Vittorio Murino ,Rita Cucchiara |
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978-3-642-33867-0 |
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ECCVW |
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IAM;ADAS; |
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IAM @ iam @ MGH2012b |
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1991 |
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Pau Cano; Alvaro Caravaca; Debora Gil; Eva Musulen |
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Title |
Diagnosis of Helicobacter pylori using AutoEncoders for the Detection of Anomalous Staining Patterns in Immunohistochemistry Images |
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Miscellaneous |
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2023 |
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Arxiv |
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107241 |
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This work addresses the detection of Helicobacter pylori a bacterium classified since 1994 as class 1 carcinogen to humans. By its highest specificity and sensitivity, the preferred diagnosis technique is the analysis of histological images with immunohistochemical staining, a process in which certain stained antibodies bind to antigens of the biological element of interest. This analysis is a time demanding task, which is currently done by an expert pathologist that visually inspects the digitized samples.
We propose to use autoencoders to learn latent patterns of healthy tissue and detect H. pylori as an anomaly in image staining. Unlike existing classification approaches, an autoencoder is able to learn patterns in an unsupervised manner (without the need of image annotations) with high performance. In particular, our model has an overall 91% of accuracy with 86\% sensitivity, 96% specificity and 0.97 AUC in the detection of H. pylori. |
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IAM |
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Admin @ si @ CCG2023 |
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3855 |
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