Detection of u-serrated patterns in direct immunofluorescence images of autoimmune bullous diseases by inhibition-augmented COSFIRE filters

[1]  A. Yuille,et al.  A Novel Linelet-Based Representation for Line Segment Detection , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Andrew H. Beck,et al.  Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer , 2017, JAMA.

[3]  Shihui Ying,et al.  Histopathological Image Classification With Color Pattern Random Binary Hashing-Based PCANet and Matrix-Form Classifier , 2017, IEEE Journal of Biomedical and Health Informatics.

[4]  Ioannis Kalatzis,et al.  Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases , 2017, Int. J. Medical Informatics.

[5]  Feng Zhou,et al.  Segmentation, Splitting, and Classification of Overlapping Bacteria in Microscope Images for Automatic Bacterial Vaginosis Diagnosis , 2017, IEEE Journal of Biomedical and Health Informatics.

[6]  Chenyu Shi,et al.  Inhibition-augmented COSFIRE model of shape-selective neurons , 2017, IBM J. Res. Dev..

[7]  R. Ludwig,et al.  Clinical features and diagnosis of epidermolysis bullosa acquisita , 2017, Expert review of clinical immunology.

[8]  George Azzopardi,et al.  Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters , 2016, Machine Vision and Applications.

[9]  Chenyu Shi,et al.  Inhibition-augmented trainable COSFIRE filters for keypoint detection and object recognition , 2016, Machine Vision and Applications.

[10]  Mihaela van der Schaar,et al.  Using Contextual Learning to Improve Diagnostic Accuracy: Application in Breast Cancer Screening , 2016, IEEE Journal of Biomedical and Health Informatics.

[11]  D. Zillikens,et al.  Automated direct immunofluorescence analyses of skin biopsies , 2016, Journal of cutaneous pathology.

[12]  Chenyu Shi,et al.  Automatic Differentiation of u- and n-serrated Patterns in Direct Immunofluorescence Images , 2015, CAIP.

[13]  George Azzopardi,et al.  Multiscale Blood Vessel Delineation Using B-COSFIRE Filters , 2015, CAIP.

[14]  M. E. Celebi,et al.  Improving Dermoscopy Image Classification Using Color Constancy , 2015, IEEE Journal of Biomedical and Health Informatics.

[15]  George Azzopardi,et al.  Trainable COSFIRE filters for vessel delineation with application to retinal images , 2015, Medical Image Anal..

[16]  Nicola Bizzaro,et al.  Automated antinuclear immunofluorescence antibody screening: a comparative study of six computer-aided diagnostic systems. , 2014, Autoimmunity reviews.

[17]  J. Meijer,et al.  The n‐ vs. u‐serration is a learnable criterion to differentiate pemphigoid from epidermolysis bullosa acquisita in direct immunofluorescence serration pattern analysis , 2013, The British journal of dermatology.

[18]  D. Zillikens,et al.  Pemphigoid diseases , 2013, The Lancet.

[19]  George Azzopardi,et al.  Trainable COSFIRE Filters for Keypoint Detection and Pattern Recognition , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  George Azzopardi,et al.  A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model , 2012, Biological Cybernetics.

[21]  M. Jonkman,et al.  The many faces of epidermolysis bullosa acquisita after serration pattern analysis by direct immunofluorescence microscopy , 2011, The British journal of dermatology.

[22]  Alireza Alaei,et al.  A new scheme for unconstrained handwritten text-line segmentation , 2011, Pattern Recognit..

[23]  Rafael Grompone von Gioi,et al.  LSD: A Fast Line Segment Detector with a False Detection Control , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Sharath Pankanti,et al.  Learning fingerprint minutiae location and type , 2003, Pattern Recognit..

[25]  Agnès Desolneux,et al.  Vanishing Point Detection without Any A Priori Information , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Kuo-Chin Fan,et al.  Fingerprint ridge allocation in direct gray-scale domain , 2001, Pattern Recognit..

[27]  Mohamed S. Kamel,et al.  A genetic algorithm for the estimation of ridges in fingerprints , 1999, IEEE Trans. Image Process..

[28]  G. F. McLean,et al.  Vanishing Point Detection by Line Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  Miguel Tavares Coimbra,et al.  Content-Adaptive Region-Based Color Texture Descriptors for Medical Images , 2017, IEEE Journal of Biomedical and Health Informatics.

[31]  George Azzopardi,et al.  Unsupervised delineation of the vessel tree in retinal fundus images , 2016 .

[32]  Chenyu Shi,et al.  Automatic Classification of Serrated Patterns in Direct Immunofluorescence Images , 2015 .

[33]  Sylvain Berlemont,et al.  Combining Local Filtering and Multiscale Analysis for Edge, Ridge, and Curvilinear Objects Detection , 2010, IEEE Transactions on Image Processing.

[34]  Kuo-Liang Chung,et al.  New orientation-based elimination approach for accurate line-detection , 2010, Pattern Recognit. Lett..

[35]  Horst Bischof,et al.  Modelling fingerprint ridge orientation using Legendre polynomials , 2010, Pattern Recognit..

[36]  R. Vodegel,et al.  Clinical and Laboratory Investigations U-serrated immunodeposition pattern differentiates type VII collagen targeting bullous diseases from other subepidermal bullous autoimmune diseases , 2004 .

[37]  Josef Smolle,et al.  Tissue counter analysis of benign common nevi and malignant melanoma , 2003, Int. J. Medical Informatics.