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This paper presents a novel lattice based biomimetic neural network trained by means of a similarity measure derived from a lattice positive valuation. For a wide class of pattern recognition problems, the proposed artificial neural network, implemented as a dendritic hetero-associative memory delivers high percentages of successful classification. The memory is a feedforward dendritic network whose arithmetical operations are based on lattice algebra and can be applied to real multivalued inputs. In this approach, the realization of recognition tasks, shows the inherent capability of prototype-class pattern associations in a fast and straightforward manner without need of any iterative scheme subject to issues about convergence. Using an artificially designed data set we show how the proposed trained neural net classifies a test input pattern. Application to a few typical real-world data sets illustrate the overall network classification performance using different training and testing sample subsets generated randomly.
Gerhard X. Ritter; Gonzalo Urcid; Luis-David Lara-Rodríguez. Similarity Measures for Learning in Lattice Based Biomimetic Neural Networks. Mathematics 2020, 8, 1439 .
AMA StyleGerhard X. Ritter, Gonzalo Urcid, Luis-David Lara-Rodríguez. Similarity Measures for Learning in Lattice Based Biomimetic Neural Networks. Mathematics. 2020; 8 (9):1439.
Chicago/Turabian StyleGerhard X. Ritter; Gonzalo Urcid; Luis-David Lara-Rodríguez. 2020. "Similarity Measures for Learning in Lattice Based Biomimetic Neural Networks." Mathematics 8, no. 9: 1439.
This paper presents a new method using discrete transforms to segment blood vessels and exudates in eye fundus color images. To obtain the desired segmentation, an illumination correction is previously done based on a homomorphic filter because of the uneven illuminance in the eye fundus image. To distinguish foreground objects from the background, we propose a super Gaussian bandpass filter in the discrete cosine transform DCT domain. These filters are applied on the green channel that contains information to segment pathologies. To segment exudates in the filtered DCT image, a gamma correction is applied to enhance foreground objects; in the resulting image, the Otsu's global threshold method is applied, after which, a masking operation over the effective area of the eye fundus image is performed to obtain the final segmentation of exudates. In the case of blood vessels, the negative of the image filtered with DCT is first calculated, then a median filter is applied to reduce noise and artifacts, followed by a gamma correction. Again, the Otsu's global threshold method for binarization, next a morphological closing operation is employed, and a masking operation gives the corresponding final segmentation. Illustrative examples taken from a free clinical database are included to demonstrate the capability of the proposed methods.
Luis David Lara Rodríguez; Gonzalo Urcid Serrano. Exudates and Blood Vessel Segmentation in Eye Fundus Images using the Fourier and Cosine Discrete Transforms. Computación y Sistemas 2016, 20, 1 .
AMA StyleLuis David Lara Rodríguez, Gonzalo Urcid Serrano. Exudates and Blood Vessel Segmentation in Eye Fundus Images using the Fourier and Cosine Discrete Transforms. Computación y Sistemas. 2016; 20 (4):1.
Chicago/Turabian StyleLuis David Lara Rodríguez; Gonzalo Urcid Serrano. 2016. "Exudates and Blood Vessel Segmentation in Eye Fundus Images using the Fourier and Cosine Discrete Transforms." Computación y Sistemas 20, no. 4: 1.
This paper presents a Fourier transform approach to detect microcalcifications in digital mammograms. The basic idea consists in the design of parametric Butterworth bandpass filters in the Fourier domain used to extract sharpened border like structures that correspond to detected mammography microcalcifications. Image thresholding of the filtered image is accomplished, first by homogenizing the background (fibroglandular tissue) with a median filter, after which a gamma correction is applied to change the global contrast. Second, by postprocessing the resulting image using histogram based local and global statistics we obtain a properly binarized image that emphasizes the desired objects (microcalcifications) and segmentation is completed using a sequence of morphological binary operations. Several illustrative examples taken from a clinical database are included to demonstrate the capability of the proposed approach in comparison with other edge detection techniques such as the difference of Gaussians (DoG) and the Laplacian of a Gaussian (LoG).
Elizabeth López-Meléndez; Luis David Lara Rodríguez; Gonzalo Urcid. Fourier-based segmentation of microcalcifications in mammograms. Applications of Digital Image Processing XXXVIII 2015, 9599, 1 .
AMA StyleElizabeth López-Meléndez, Luis David Lara Rodríguez, Gonzalo Urcid. Fourier-based segmentation of microcalcifications in mammograms. Applications of Digital Image Processing XXXVIII. 2015; 9599 ():1.
Chicago/Turabian StyleElizabeth López-Meléndez; Luis David Lara Rodríguez; Gonzalo Urcid. 2015. "Fourier-based segmentation of microcalcifications in mammograms." Applications of Digital Image Processing XXXVIII 9599, no. : 1.
Gonzalo Urcid; Luis David Lara Rodríguez; Elizabeth López-Meléndez. A dendritic lattice neural network for color image segmentation. Applications of Digital Image Processing XXXVIII 2015, 95992O -95992O-10.
AMA StyleGonzalo Urcid, Luis David Lara Rodríguez, Elizabeth López-Meléndez. A dendritic lattice neural network for color image segmentation. Applications of Digital Image Processing XXXVIII. 2015; ():95992O-95992O-10.
Chicago/Turabian StyleGonzalo Urcid; Luis David Lara Rodríguez; Elizabeth López-Meléndez. 2015. "A dendritic lattice neural network for color image segmentation." Applications of Digital Image Processing XXXVIII , no. : 95992O-95992O-10.
Luis David Lara Rodríguez; Elizabeth López-Meléndez; Jorge M. Ibarra Galitzia; Estela López-Olazagasti; Eduardo Tepichín-Rodríguez. Reconstruction of tridimensional objects with two different textures using Gaussian model. Optical Engineering + Applications 2012, 84992A -84992A-9.
AMA StyleLuis David Lara Rodríguez, Elizabeth López-Meléndez, Jorge M. Ibarra Galitzia, Estela López-Olazagasti, Eduardo Tepichín-Rodríguez. Reconstruction of tridimensional objects with two different textures using Gaussian model. Optical Engineering + Applications. 2012; ():84992A-84992A-9.
Chicago/Turabian StyleLuis David Lara Rodríguez; Elizabeth López-Meléndez; Jorge M. Ibarra Galitzia; Estela López-Olazagasti; Eduardo Tepichín-Rodríguez. 2012. "Reconstruction of tridimensional objects with two different textures using Gaussian model." Optical Engineering + Applications , no. : 84992A-84992A-9.
The Breast Imaging Reporting and Data System (BIRADS) was developed by the American College of Radiologists as a standard of comparison for rating mammograms and breast ultrasound images. It sets up a classification for the Level of Suspicion (LOS) of the possibility of a breast cancer. In this paper we present an automated image analyzing system that finds calcifications based on the standard BIRADS 1 and 2. For our goal, we studied the digital mammography database in DICOM format provided by the Department of Radiology of the Hospital Universitario de Puebla. We used The Difference of Gaussian (DOG) filter to find edges of the forms of the different calcifications and a back-propagation Artificial Neural Network (ANN) for the pattern recognition of the BIRADS 1 and 2 cases. This method allowed us to automate the segmentation of the calcifications with a low computational cost. We achieved the pattern recognition with a high level of sensitivity of 0.9629 and specificity of 0.9920.
Elizabeth López-Meléndez; Luis David Lara Rodríguez; Estela López-Olazagasti; Barbara Sanchez-Rinza; Eduardo Tepichín-Rodriguez. BICAD: Breast image computer aided diagnosis for standard BIRADS 1 and 2 in calcifications. CONIELECOMP 2012, 22nd International Conference on Electrical Communications and Computers 2012, 190 -195.
AMA StyleElizabeth López-Meléndez, Luis David Lara Rodríguez, Estela López-Olazagasti, Barbara Sanchez-Rinza, Eduardo Tepichín-Rodriguez. BICAD: Breast image computer aided diagnosis for standard BIRADS 1 and 2 in calcifications. CONIELECOMP 2012, 22nd International Conference on Electrical Communications and Computers. 2012; ():190-195.
Chicago/Turabian StyleElizabeth López-Meléndez; Luis David Lara Rodríguez; Estela López-Olazagasti; Barbara Sanchez-Rinza; Eduardo Tepichín-Rodriguez. 2012. "BICAD: Breast image computer aided diagnosis for standard BIRADS 1 and 2 in calcifications." CONIELECOMP 2012, 22nd International Conference on Electrical Communications and Computers , no. : 190-195.