IEEE International Conference on Image Processing 2005, 2005
The common approach to image matching is to detect spatial features present in both images and cr... more The common approach to image matching is to detect spatial features present in both images and create a mapping that relates both images. The main drawback of this method takes place when more than one matching is likely. A first simplification to this ambiguity is to represent with a parametric model the point locus where the matching is highly likely, and then use a POCS (projection onto convex sets) procedure combined with Tikhonov regularization that results in the mapping vectors. However, if there is more than one model per pixel, the regularization and constraintforcing process faces a multiple-choice dilemma that has no easy solution. This work proposes a framework to overcome this drawback: the combined projection over multiple models based on the L k norm of the projection-point distance. This approach is tested on a stereo-pair that presents multiple choices of similar likelihood.
IEEE International Conference on Image Processing 2005, 2005
Abstract Artificial muscles are formed by attaching a conducting polymeric film to a non-conducti... more Abstract Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. The flow of an electric current produces a macroscopic bending movement on the muscle. A good characterization of both, motion rate and energy of curvature, is ...
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003
Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. A... more Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. Applying an electrical current on the muscle. a macroscopic bending movement appears on it. Study of curvature variations and related parameters, such as speed of motion or energy of curvature, is necessary for improving the efficiency of these devices. In a previous work. a one-cam computer vision system was developed to estimate motion parameters in 2D with precise results. In this paper, a two-cam stereo vision system is proposed to process the image sequence and track the muscle in 3D. Active contours models are employed in motion detection and mechanical parameters estimation. Results prove the validity of this approach, allowing automatic testing on the research into artificial muscles.
ABSTRACT This paper describes the image registration block developed in the hepatic planner HepaP... more ABSTRACT This paper describes the image registration block developed in the hepatic planner HepaPlan. The proposed method is intended to support clinical decisions about treatment of liver pathologies. The initial stage is the segmentation of the liver tissue as well as its internal structures and tumours in contrast-enhanced CT volumes. The second stage is non-rigid motion compensation due to CT data are acquired at different times, in arterial phase and venous phase. This image registration is necessary in order to fusion contrast-enhanced CT data and then to ease 3D volumetric measures, visualization of the liver and tumour, and to make comparisons with studies of the same patient at earlier times.
Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, 2015
This paper describes a new approach to compute bifurcation angles in retinal images. This approac... more This paper describes a new approach to compute bifurcation angles in retinal images. This approach is based on the estimation of multiple orientations at each pixel of a gray retinal image. The main orientations are provided by directional openings whose outputs are regularized in order to extend the orientation information to the whole image. The detection of vessel bifurcations is based on the coexistence of two or more than two different main orientations at the same pixel. Once the bifurcations and crossovers has been identified, bifurcation angles are calculated. The proposed procedure of computing bifurcation angles by means of orientation estimation at all pixels of the gray level image is much more stable than those methods which are based on the skeleton of the vascular tree, since a slight variation of a pixel of the skeleton can produce a significant change in the angle value.
2010 Ieee International Conference on Image Processing, 2010
... 6(c)), whereas for the other test images the estimated IMT presents a considerable lower di-f... more ... 6(c)), whereas for the other test images the estimated IMT presents a considerable lower di-fference with respect to the doctor's IMT measurement. 6. REFERENCES ... 10, no. 2, pp. 215233, April 2006. [8] M. Ceccarelli, N. De Luca, and A. Morganella, Automatic measurement ...
Many real-word classification scenarios suffer a common drawback: missing, or incomplete, data. T... more Many real-word classification scenarios suffer a common drawback: missing, or incomplete, data. The ability of missing data handling has become a fundamental requirement for pattern classification because the absence of certain values for relevant data attributes can seriously affect the accuracy of classification results. This chapter focuses on incomplete pattern classification. The research works on this topic currently grows wider and it is well known how useful and efficient are most of the solutions based on machine learning. This chapter analyzes the most popular and proper missing data techniques based on machine learning for solving pattern classification tasks, trying to highlight their advantages and disadvantages.
Boundary detection has a relevant importance in locomotor system ecographies, mainly because some... more Boundary detection has a relevant importance in locomotor system ecographies, mainly because some illnesses and injuries can be detected before the first symptoms appear. The images used show a great variety of textures as well as non clear edges. This drawback may result in different contours depending on the person who traces them out and different diagnoses too. This paper
Segmentation of carotid artery lumen in two-dimensional and three-dimensional ultrasonography is ... more Segmentation of carotid artery lumen in two-dimensional and three-dimensional ultrasonography is an important step in computerized evaluation of arterial disease severity and in finding vulnerable atherosclerotic plaques susceptible to rupture causing stroke. Because of the complexity of anatomical structures, noise as well as the requirement of accurate segmentation, interactions are necessary between observers and the computer segmentation process. In this paper a segmentation process is described based on the deformable model method with only one seed point to guide the initialization of the deformable model for each lumen cross section. With one seed, the initial contour of the deformable model is generated using the entropy map of the original image and mathematical morphology operations. The deformable model is driven to fit the lumen contour by an internal force and an external force that are calculated, respectively, with geometrical properties of deformed contour and with the image gray level features. The evaluation methodology using distance-based and area-based metrics is introduced in this paper. A contour probability distribution (CPD) method for calculating distance-based metrics is introduced. The CPD is obtained by generating contours of the lumen using a set of possible seed locations. The mean contour can be compared to a manual outlined contour to provide accuracy metrics. The variance computed from the CPD can provide metrics of local and global variability. These metrics provide a complete performance evaluation of an interactive segmentation algorithm and a means for comparing different algorithm settings.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004
Active deformable models are simple tools, very popular in computer vision and computer graphics,... more Active deformable models are simple tools, very popular in computer vision and computer graphics, for solving ill-posed problems or mimic real physical systems. The classical formulation is given in the spatial domain, the motor of the procedure is a second-order linear system, and rigidity and elasticity are the basic parameters for its characterization. This paper proposes a novel formulation based on a frequency-domain analysis: The internal energy functional and the Lagrange minimization are performed entirely in the frequency domain, which leads to a simple formulation and design. The frequency-based implementation offers important computational savings in comparison to the original one, a feature that is improved by the efficient hardware and software computation of the FFT algorithm. This new formulation focuses on the stiffness spectrum, allowing the possibility of constructing deformable models apart from the elasticity and rigidity-based original formulation. Simulation examples validate the theoretical results.
ABSTRACT In this paper, a novel theoretical framework defined in the frequency domain for variati... more ABSTRACT In this paper, a novel theoretical framework defined in the frequency domain for variational non-parametric image registration is proposed. It provides more efficient implementations than existing theoretical approaches for the most common registration techniques. The presented frequency domain analysis adds simplicity to the variational image registration implementations and allows for an easy extension to higher dimensions by using the multidimensional Fourier transform of multidimensional signals. Este trabajo está financiado por el Ministerio de Ciencia y Tecnoloíıa, bajo el proyecto TEC2006-13338/TCM .
The presence of metal artifacts in dental CT prevents the correct exploration and planning of den... more The presence of metal artifacts in dental CT prevents the correct exploration and planning of dental interventions. This paper addresses a new paradigm in metal artifact reduction that uses the backprojected data available in the DICOM files. The method, based on variational image registration and morphological lambda reconstruction, enhances the image quality using not only the information of the artifacted
IEEE International Conference on Image Processing 2005, 2005
The common approach to image matching is to detect spatial features present in both images and cr... more The common approach to image matching is to detect spatial features present in both images and create a mapping that relates both images. The main drawback of this method takes place when more than one matching is likely. A first simplification to this ambiguity is to represent with a parametric model the point locus where the matching is highly likely, and then use a POCS (projection onto convex sets) procedure combined with Tikhonov regularization that results in the mapping vectors. However, if there is more than one model per pixel, the regularization and constraintforcing process faces a multiple-choice dilemma that has no easy solution. This work proposes a framework to overcome this drawback: the combined projection over multiple models based on the L k norm of the projection-point distance. This approach is tested on a stereo-pair that presents multiple choices of similar likelihood.
IEEE International Conference on Image Processing 2005, 2005
Abstract Artificial muscles are formed by attaching a conducting polymeric film to a non-conducti... more Abstract Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. The flow of an electric current produces a macroscopic bending movement on the muscle. A good characterization of both, motion rate and energy of curvature, is ...
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003
Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. A... more Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. Applying an electrical current on the muscle. a macroscopic bending movement appears on it. Study of curvature variations and related parameters, such as speed of motion or energy of curvature, is necessary for improving the efficiency of these devices. In a previous work. a one-cam computer vision system was developed to estimate motion parameters in 2D with precise results. In this paper, a two-cam stereo vision system is proposed to process the image sequence and track the muscle in 3D. Active contours models are employed in motion detection and mechanical parameters estimation. Results prove the validity of this approach, allowing automatic testing on the research into artificial muscles.
ABSTRACT This paper describes the image registration block developed in the hepatic planner HepaP... more ABSTRACT This paper describes the image registration block developed in the hepatic planner HepaPlan. The proposed method is intended to support clinical decisions about treatment of liver pathologies. The initial stage is the segmentation of the liver tissue as well as its internal structures and tumours in contrast-enhanced CT volumes. The second stage is non-rigid motion compensation due to CT data are acquired at different times, in arterial phase and venous phase. This image registration is necessary in order to fusion contrast-enhanced CT data and then to ease 3D volumetric measures, visualization of the liver and tumour, and to make comparisons with studies of the same patient at earlier times.
Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, 2015
This paper describes a new approach to compute bifurcation angles in retinal images. This approac... more This paper describes a new approach to compute bifurcation angles in retinal images. This approach is based on the estimation of multiple orientations at each pixel of a gray retinal image. The main orientations are provided by directional openings whose outputs are regularized in order to extend the orientation information to the whole image. The detection of vessel bifurcations is based on the coexistence of two or more than two different main orientations at the same pixel. Once the bifurcations and crossovers has been identified, bifurcation angles are calculated. The proposed procedure of computing bifurcation angles by means of orientation estimation at all pixels of the gray level image is much more stable than those methods which are based on the skeleton of the vascular tree, since a slight variation of a pixel of the skeleton can produce a significant change in the angle value.
2010 Ieee International Conference on Image Processing, 2010
... 6(c)), whereas for the other test images the estimated IMT presents a considerable lower di-f... more ... 6(c)), whereas for the other test images the estimated IMT presents a considerable lower di-fference with respect to the doctor's IMT measurement. 6. REFERENCES ... 10, no. 2, pp. 215233, April 2006. [8] M. Ceccarelli, N. De Luca, and A. Morganella, Automatic measurement ...
Many real-word classification scenarios suffer a common drawback: missing, or incomplete, data. T... more Many real-word classification scenarios suffer a common drawback: missing, or incomplete, data. The ability of missing data handling has become a fundamental requirement for pattern classification because the absence of certain values for relevant data attributes can seriously affect the accuracy of classification results. This chapter focuses on incomplete pattern classification. The research works on this topic currently grows wider and it is well known how useful and efficient are most of the solutions based on machine learning. This chapter analyzes the most popular and proper missing data techniques based on machine learning for solving pattern classification tasks, trying to highlight their advantages and disadvantages.
Boundary detection has a relevant importance in locomotor system ecographies, mainly because some... more Boundary detection has a relevant importance in locomotor system ecographies, mainly because some illnesses and injuries can be detected before the first symptoms appear. The images used show a great variety of textures as well as non clear edges. This drawback may result in different contours depending on the person who traces them out and different diagnoses too. This paper
Segmentation of carotid artery lumen in two-dimensional and three-dimensional ultrasonography is ... more Segmentation of carotid artery lumen in two-dimensional and three-dimensional ultrasonography is an important step in computerized evaluation of arterial disease severity and in finding vulnerable atherosclerotic plaques susceptible to rupture causing stroke. Because of the complexity of anatomical structures, noise as well as the requirement of accurate segmentation, interactions are necessary between observers and the computer segmentation process. In this paper a segmentation process is described based on the deformable model method with only one seed point to guide the initialization of the deformable model for each lumen cross section. With one seed, the initial contour of the deformable model is generated using the entropy map of the original image and mathematical morphology operations. The deformable model is driven to fit the lumen contour by an internal force and an external force that are calculated, respectively, with geometrical properties of deformed contour and with the image gray level features. The evaluation methodology using distance-based and area-based metrics is introduced in this paper. A contour probability distribution (CPD) method for calculating distance-based metrics is introduced. The CPD is obtained by generating contours of the lumen using a set of possible seed locations. The mean contour can be compared to a manual outlined contour to provide accuracy metrics. The variance computed from the CPD can provide metrics of local and global variability. These metrics provide a complete performance evaluation of an interactive segmentation algorithm and a means for comparing different algorithm settings.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004
Active deformable models are simple tools, very popular in computer vision and computer graphics,... more Active deformable models are simple tools, very popular in computer vision and computer graphics, for solving ill-posed problems or mimic real physical systems. The classical formulation is given in the spatial domain, the motor of the procedure is a second-order linear system, and rigidity and elasticity are the basic parameters for its characterization. This paper proposes a novel formulation based on a frequency-domain analysis: The internal energy functional and the Lagrange minimization are performed entirely in the frequency domain, which leads to a simple formulation and design. The frequency-based implementation offers important computational savings in comparison to the original one, a feature that is improved by the efficient hardware and software computation of the FFT algorithm. This new formulation focuses on the stiffness spectrum, allowing the possibility of constructing deformable models apart from the elasticity and rigidity-based original formulation. Simulation examples validate the theoretical results.
ABSTRACT In this paper, a novel theoretical framework defined in the frequency domain for variati... more ABSTRACT In this paper, a novel theoretical framework defined in the frequency domain for variational non-parametric image registration is proposed. It provides more efficient implementations than existing theoretical approaches for the most common registration techniques. The presented frequency domain analysis adds simplicity to the variational image registration implementations and allows for an easy extension to higher dimensions by using the multidimensional Fourier transform of multidimensional signals. Este trabajo está financiado por el Ministerio de Ciencia y Tecnoloíıa, bajo el proyecto TEC2006-13338/TCM .
The presence of metal artifacts in dental CT prevents the correct exploration and planning of den... more The presence of metal artifacts in dental CT prevents the correct exploration and planning of dental interventions. This paper addresses a new paradigm in metal artifact reduction that uses the backprojected data available in the DICOM files. The method, based on variational image registration and morphological lambda reconstruction, enhances the image quality using not only the information of the artifacted
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