International Conference on Pattern Recognition, 2010
Decomposition methods are multiclass classification schemes where the polychotomy is reduced into... more Decomposition methods are multiclass classification schemes where the polychotomy is reduced into several dichotomies. Each dichotomy is addressed by a classifier trained on a training set derived from the original one on the basis of the decomposition rule adopted. These new training sets may present a disproportion between the classes, harming the global recognition accuracy. Indeed, traditional learning algorithms are
IEEE Symposium on Computer-Based Medical Systems, 2011
Indirect immunofluorescence (IIF) is the recommended technique to detect rheumatic diseases throu... more Indirect immunofluorescence (IIF) is the recommended technique to detect rheumatic diseases through the analysis of images exhibiting a fluorescence in the green band. Since the request of such tests has recently increased, researches efforts have been directed towards the development of computer-aided diagnosis (CAD) tools supporting the specialists and improving the standardization of the method. Technological advances have made available
ABSTRACT Objective: Computed tomography images are becoming an invaluable mean for abdominal orga... more ABSTRACT Objective: Computed tomography images are becoming an invaluable mean for abdominal organ investigation. In the field of medical image processing, some of the current interests are the automatic diagnosis of liver, spleen, and kidney pathologies, and ...
IEEE Symposium on Computer-Based Medical Systems, 2011
Photobleaching effect is a major issue in developing autofocus algorithms for indirect immunofluo... more Photobleaching effect is a major issue in developing autofocus algorithms for indirect immunofluorescence (IIF) assay since it quickly flattens the fluorescence intensity of the samples. To overcome this limitation we propose an autofocus algorithm, suited for IIF, aiming at minimizing the number of images required to focus the sample. We test our algorithm with an heterogeneous set of IIF images
International Joint Conference on Biomedical Engineering Systems and Technologies, 2008
Polychotomies are recognition tasks with a number of categories greater than two, consisting in a... more Polychotomies are recognition tasks with a number of categories greater than two, consisting in assigning patterns to a finite set of classes. Although many of the learning algorithms developed so far are capable of handling polychotomies, most of them were designed by nature for dichotomies, that is, for binary learning. Therefore, various methods that decompose the multiclass recognition task in
International Conference on Image Analysis and Processing, 2009
Autoantibody tests based on Crithidia Luciliae (CL) substrate are the recommended method to detec... more Autoantibody tests based on Crithidia Luciliae (CL) substrate are the recommended method to detect Systemic Lupus Erythematosus (SLE), a very serious sickness further to be classified as an invalidating chronic disease. CL is an unicellular organism containing a strongly tangled mass of circular dsDNA, named as kinetoplast, whose fluorescence determines the positiveness to the test. Conversely, the staining of other
IEEE Symposium on Computer-Based Medical Systems, 2010
Detection of antibodies via indirect immunofluorescence (IIF) is a common marker in patients with... more Detection of antibodies via indirect immunofluorescence (IIF) is a common marker in patients with suspected connective tissue diseases. IIF readings are affected by several issues limiting their reproducibility and reliability: hence, the development of a computer-aided diagnosis (CAD) tool supporting IIF diagnostic procedure would be beneficial in many respects. Although some works in the literature use greyscale cooled cameras for
IEEE Symposium on Computer-Based Medical Systems, 2010
Indirect immunofluorescence (IIF) imaging is the recommended laboratory technique to detect autoa... more Indirect immunofluorescence (IIF) imaging is the recommended laboratory technique to detect autoantibodies in patient serum, but it suffers from several issues limiting its reliability and reproducibility. IIF slides are observed by specialists at the fluorescence microscope, reporting fluorescence intensity and staining pattern and looking for mitotic cells. Indeed, the presence of such cells is a key factor to assess the
IEEE Symposium on Computer-Based Medical Systems, 2009
Learning under imbalanced dataset can be difficult since traditional algorithms are biased toward... more Learning under imbalanced dataset can be difficult since traditional algorithms are biased towards the majority class, providing low predictive accuracy over the minority one. Among the several methods proposed in the literature to overcome such a limitation, the most recent uses multi-experts system (MES) composed of balanced classifiers, whose decisions are aggregated according to a combination rule. Each classifier of
Typical pattern recognition applications require to handle both binary and multiclass classificat... more Typical pattern recognition applications require to handle both binary and multiclass classification problems. Several researchers have pointed out that obtaining a classifier that discriminates between two classes is much easier than building one that simultaneously distinguishes among all classes. This observation has motivated substantial research on using a pool of binary classifiers to address multiclass problems. Such an approach is
International Conference on Image Analysis and Processing, 2007
In autoimmune diseases, HEp-2 cells are used to detect antinuclear autoantibodies through indirec... more In autoimmune diseases, HEp-2 cells are used to detect antinuclear autoantibodies through indirect immunofluorescence (IIF) method. These cells can reveal different staining patterns that are relevant to diagnostic purposes. To classify them highly specialized personnel are required, who are not always available. In this respect, a medical demand is the development of a recognition system supporting such an activity. In
IEEE Symposium on Computer-Based Medical Systems, 2007
In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for d... more In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for detection of antinuclear autoantibodies (ANA). IIF diagnosis requires both the estimation of fluorescence intensity and the description of staining pattern, demanding for highly specialized personnel, who are not always available. In this respect, computer-aided diagnosis (CAD) tools can support physicians' decision. In this paper we report experiences in the
Communications in Computer and Information Science, 2009
Polychotomies are recognition tasks with a number of categories greater than two, consisting in a... more Polychotomies are recognition tasks with a number of categories greater than two, consisting in assigning patterns to a finite set of classes. Although many of the learning algorithms developed so far are capable of handling polychotomies, most of them were designed by nature for dichotomies, that is, for binary learning. Therefore, various methods that decompose the multiclass recognition task in
ABSTRACT Several binary classification problems exhibit imbalance in class distribution, influenc... more ABSTRACT Several binary classification problems exhibit imbalance in class distribution, influencing system learning. Indeed, traditional machine learning algorithms are biased towards the majority class, thus producing poor predictive accuracy over the minority one. To overcome this limitation, many approaches have been proposed up to now to build artificially balanced training sets. Further to their specific drawbacks, they achieve more balanced accuracies on each class harming the global accuracy. This paper first reviews the more recent method coping with imbalanced datasets and then proposes a strategy overcoming the main drawbacks of existing approaches. It is based on an ensemble of classifiers trained on balanced subsets of the original imbalanced training set working in conjunction with the classifier trained on the original imbalanced dataset. The performance of the method has been estimated on six public datasets, proving its effectiveness also in comparison with other approaches. It also gives the chance to modify the system behaviour according to the operating scenario.
Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007
In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for d... more In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for detection of antinuclear autoantibodies (ANA). IIF diagnosis requires both the estimation of fluorescence intensity and the description of staining pattern, demanding for highly specialized personnel, who are not always available. In this respect, computer-aided diagnosis (CAD) tools can support physicians' decision. In this paper we report experiences in the staining pattern recognition of IIF wells. Since several cells constitute each well, we have developed a multiple expert system (MES) devised to classify the pattern of individual cells. The whole well staining pattern is computed on the strength of the recognition of its cells, testing two aggregation rules. The experimental results shows the feasibility of a CAD dedicated to the classification of staining pattern in the IIF field.
2009 22nd IEEE International Symposium on Computer-Based Medical Systems, 2009
Learning under imbalanced dataset can be difficult since traditional algorithms are biased toward... more Learning under imbalanced dataset can be difficult since traditional algorithms are biased towards the majority class, providing low predictive accuracy over the minority one. Among the several methods proposed in the literature to overcome such a limitation, the most recent uses multi-experts system (MES) composed of balanced classifiers, whose decisions are aggregated according to a combination rule. Each classifier of
International Conference on Pattern Recognition, 2010
Decomposition methods are multiclass classification schemes where the polychotomy is reduced into... more Decomposition methods are multiclass classification schemes where the polychotomy is reduced into several dichotomies. Each dichotomy is addressed by a classifier trained on a training set derived from the original one on the basis of the decomposition rule adopted. These new training sets may present a disproportion between the classes, harming the global recognition accuracy. Indeed, traditional learning algorithms are
IEEE Symposium on Computer-Based Medical Systems, 2011
Indirect immunofluorescence (IIF) is the recommended technique to detect rheumatic diseases throu... more Indirect immunofluorescence (IIF) is the recommended technique to detect rheumatic diseases through the analysis of images exhibiting a fluorescence in the green band. Since the request of such tests has recently increased, researches efforts have been directed towards the development of computer-aided diagnosis (CAD) tools supporting the specialists and improving the standardization of the method. Technological advances have made available
ABSTRACT Objective: Computed tomography images are becoming an invaluable mean for abdominal orga... more ABSTRACT Objective: Computed tomography images are becoming an invaluable mean for abdominal organ investigation. In the field of medical image processing, some of the current interests are the automatic diagnosis of liver, spleen, and kidney pathologies, and ...
IEEE Symposium on Computer-Based Medical Systems, 2011
Photobleaching effect is a major issue in developing autofocus algorithms for indirect immunofluo... more Photobleaching effect is a major issue in developing autofocus algorithms for indirect immunofluorescence (IIF) assay since it quickly flattens the fluorescence intensity of the samples. To overcome this limitation we propose an autofocus algorithm, suited for IIF, aiming at minimizing the number of images required to focus the sample. We test our algorithm with an heterogeneous set of IIF images
International Joint Conference on Biomedical Engineering Systems and Technologies, 2008
Polychotomies are recognition tasks with a number of categories greater than two, consisting in a... more Polychotomies are recognition tasks with a number of categories greater than two, consisting in assigning patterns to a finite set of classes. Although many of the learning algorithms developed so far are capable of handling polychotomies, most of them were designed by nature for dichotomies, that is, for binary learning. Therefore, various methods that decompose the multiclass recognition task in
International Conference on Image Analysis and Processing, 2009
Autoantibody tests based on Crithidia Luciliae (CL) substrate are the recommended method to detec... more Autoantibody tests based on Crithidia Luciliae (CL) substrate are the recommended method to detect Systemic Lupus Erythematosus (SLE), a very serious sickness further to be classified as an invalidating chronic disease. CL is an unicellular organism containing a strongly tangled mass of circular dsDNA, named as kinetoplast, whose fluorescence determines the positiveness to the test. Conversely, the staining of other
IEEE Symposium on Computer-Based Medical Systems, 2010
Detection of antibodies via indirect immunofluorescence (IIF) is a common marker in patients with... more Detection of antibodies via indirect immunofluorescence (IIF) is a common marker in patients with suspected connective tissue diseases. IIF readings are affected by several issues limiting their reproducibility and reliability: hence, the development of a computer-aided diagnosis (CAD) tool supporting IIF diagnostic procedure would be beneficial in many respects. Although some works in the literature use greyscale cooled cameras for
IEEE Symposium on Computer-Based Medical Systems, 2010
Indirect immunofluorescence (IIF) imaging is the recommended laboratory technique to detect autoa... more Indirect immunofluorescence (IIF) imaging is the recommended laboratory technique to detect autoantibodies in patient serum, but it suffers from several issues limiting its reliability and reproducibility. IIF slides are observed by specialists at the fluorescence microscope, reporting fluorescence intensity and staining pattern and looking for mitotic cells. Indeed, the presence of such cells is a key factor to assess the
IEEE Symposium on Computer-Based Medical Systems, 2009
Learning under imbalanced dataset can be difficult since traditional algorithms are biased toward... more Learning under imbalanced dataset can be difficult since traditional algorithms are biased towards the majority class, providing low predictive accuracy over the minority one. Among the several methods proposed in the literature to overcome such a limitation, the most recent uses multi-experts system (MES) composed of balanced classifiers, whose decisions are aggregated according to a combination rule. Each classifier of
Typical pattern recognition applications require to handle both binary and multiclass classificat... more Typical pattern recognition applications require to handle both binary and multiclass classification problems. Several researchers have pointed out that obtaining a classifier that discriminates between two classes is much easier than building one that simultaneously distinguishes among all classes. This observation has motivated substantial research on using a pool of binary classifiers to address multiclass problems. Such an approach is
International Conference on Image Analysis and Processing, 2007
In autoimmune diseases, HEp-2 cells are used to detect antinuclear autoantibodies through indirec... more In autoimmune diseases, HEp-2 cells are used to detect antinuclear autoantibodies through indirect immunofluorescence (IIF) method. These cells can reveal different staining patterns that are relevant to diagnostic purposes. To classify them highly specialized personnel are required, who are not always available. In this respect, a medical demand is the development of a recognition system supporting such an activity. In
IEEE Symposium on Computer-Based Medical Systems, 2007
In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for d... more In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for detection of antinuclear autoantibodies (ANA). IIF diagnosis requires both the estimation of fluorescence intensity and the description of staining pattern, demanding for highly specialized personnel, who are not always available. In this respect, computer-aided diagnosis (CAD) tools can support physicians' decision. In this paper we report experiences in the
Communications in Computer and Information Science, 2009
Polychotomies are recognition tasks with a number of categories greater than two, consisting in a... more Polychotomies are recognition tasks with a number of categories greater than two, consisting in assigning patterns to a finite set of classes. Although many of the learning algorithms developed so far are capable of handling polychotomies, most of them were designed by nature for dichotomies, that is, for binary learning. Therefore, various methods that decompose the multiclass recognition task in
ABSTRACT Several binary classification problems exhibit imbalance in class distribution, influenc... more ABSTRACT Several binary classification problems exhibit imbalance in class distribution, influencing system learning. Indeed, traditional machine learning algorithms are biased towards the majority class, thus producing poor predictive accuracy over the minority one. To overcome this limitation, many approaches have been proposed up to now to build artificially balanced training sets. Further to their specific drawbacks, they achieve more balanced accuracies on each class harming the global accuracy. This paper first reviews the more recent method coping with imbalanced datasets and then proposes a strategy overcoming the main drawbacks of existing approaches. It is based on an ensemble of classifiers trained on balanced subsets of the original imbalanced training set working in conjunction with the classifier trained on the original imbalanced dataset. The performance of the method has been estimated on six public datasets, proving its effectiveness also in comparison with other approaches. It also gives the chance to modify the system behaviour according to the operating scenario.
Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007
In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for d... more In autoimmune diseases, indirect immunofluorescence (IIF) represents the recommended method for detection of antinuclear autoantibodies (ANA). IIF diagnosis requires both the estimation of fluorescence intensity and the description of staining pattern, demanding for highly specialized personnel, who are not always available. In this respect, computer-aided diagnosis (CAD) tools can support physicians' decision. In this paper we report experiences in the staining pattern recognition of IIF wells. Since several cells constitute each well, we have developed a multiple expert system (MES) devised to classify the pattern of individual cells. The whole well staining pattern is computed on the strength of the recognition of its cells, testing two aggregation rules. The experimental results shows the feasibility of a CAD dedicated to the classification of staining pattern in the IIF field.
2009 22nd IEEE International Symposium on Computer-Based Medical Systems, 2009
Learning under imbalanced dataset can be difficult since traditional algorithms are biased toward... more Learning under imbalanced dataset can be difficult since traditional algorithms are biased towards the majority class, providing low predictive accuracy over the minority one. Among the several methods proposed in the literature to overcome such a limitation, the most recent uses multi-experts system (MES) composed of balanced classifiers, whose decisions are aggregated according to a combination rule. Each classifier of
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