NURBS functional network approach for automatic image segmentation of macroscopic medical images in melanoma detection
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Iztok Fister | Akemi Gálvez | César Otero | Andrés Iglesias | José A. Díaz | Iztok Fister | A. Gálvez | C. Otero | Andrés Iglesias
[1] Juvenal Rodríguez-Reséndiz,et al. A High-Accuracy Mathematical Morphology and Multilayer Perceptron-Based Approach for Melanoma Detection , 2020, Applied Sciences.
[2] Iztok Fister,et al. Cuckoo Search Algorithm for Border Reconstruction of Medical Images with Rational Curves , 2019, ICSI.
[3] Iztok Fister,et al. Computing rational border curves of melanoma and other skin lesions from medical images with bat algorithm , 2019, GECCO.
[4] K. P. Sanal Kumar,et al. Detection of Skin Cancer Using SVM, Random Forest and kNN Classifiers , 2019, Journal of Medical Systems.
[5] Iztok Fister,et al. Hybrid Modified Firefly Algorithm for Border Detection of Skin Lesions in Medical Imaging , 2019, 2019 IEEE Congress on Evolutionary Computation (CEC).
[6] Iztok Fister,et al. Automatic Fitting of Feature Points for Border Detection of Skin Lesions in Medical Images with Bat Algorithm , 2018, IDC.
[7] R Ramya Ravi,et al. Artifacts Removal in Melanoma Using Various Preprocessing Filters , 2018, International Journal of Engineering & Technology.
[8] Navid Razmjooy,et al. A Hybrid Neural Network – World Cup Optimization Algorithm for Melanoma Detection , 2018, Open medicine.
[9] Josline Elsa Joseph,et al. A comparison of filtering and enhancement methods in malignant melanoma images , 2017, 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI).
[10] Zhen Ma,et al. A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model , 2016, IEEE Journal of Biomedical and Health Informatics.
[11] Marcel F. Jonkman,et al. MED-NODE: A computer-assisted melanoma diagnosis system using non-dermoscopic images , 2015, Expert Syst. Appl..
[12] Reza Azmi,et al. Automated lesion border detection of dermoscopy images using spectral clustering , 2015, 2015 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA).
[13] Wooi-Haw Tan,et al. Combined Spline and B-spline for an Improved Automatic Skin Lesion Segmentation in Dermoscopic Images Using Optimal Color Channel , 2014, Journal of Medical Systems.
[14] Gilson A. Giraldi,et al. Multi-object segmentation approach based on topological derivative and level set method , 2011, Integr. Comput. Aided Eng..
[15] Ezzeddine Zagrouba,et al. A PRELIMARY APPROACH FOR THE AUTOMATED RECOGNITION OF MALIGNANT MELANOMA , 2011 .
[16] Mohammad Aldeen,et al. Border detection in dermoscopy images using hybrid thresholding on optimized color channels , 2011, Comput. Medical Imaging Graph..
[17] J. Shanbehzadeh,et al. Melanoma Diagnosis by the Use of Wavelet Analysis based on Morphological Operators , 2011 .
[18] Martin Ester,et al. Graph-based pigment network detection in skin images , 2010, Medical Imaging.
[19] M. Emin Yüksel,et al. Accurate Segmentation of Dermoscopic Images by Image Thresholding Based on Type-2 Fuzzy Logic , 2009, IEEE Transactions on Fuzzy Systems.
[20] Ning Situ,et al. A narrow band graph partitioning method for skin lesion segmentation , 2009, Pattern Recognit..
[21] Gerald Schaefer,et al. Lesion border detection in dermoscopy images , 2009, Comput. Medical Imaging Graph..
[22] Gerald Schaefer,et al. Anisotropic Mean Shift Based Fuzzy C-Means Segmentation of Dermoscopy Images , 2009, IEEE Journal of Selected Topics in Signal Processing.
[23] R. H. Moss,et al. Border detection in dermoscopy images using statistical region merging , 2008, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.
[24] Andrés Iglesias,et al. Numerical-Symbolic Matlab Toolbox for Computer Graphics and Differential Geometry , 2005, ICCSA.
[25] P. Schmid. Segmentation of digitized dermatoscopic images by two-dimensional color clustering , 1999, IEEE Transactions on Medical Imaging.
[26] Enrique Castillo,et al. Functional Networks , 1998, Neural Processing Letters.
[27] A. Iglesias,et al. A package for symbolic solution of real functional equations of real variables , 1997 .
[28] W. Stolz,et al. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. , 1994, Journal of the American Academy of Dermatology.
[29] A. Kopf,et al. Early detection of malignant melanoma: The role of physician examination and self‐examination of the skin , 1985, CA: a cancer journal for clinicians.
[30] Iztok Fister,et al. Functional Networks for Image Segmentation of Cutaneous Lesions with Rational Curves , 2020, Soft Computing Models in Industrial and Environmental Applications.
[31] Andrés Iglesias,et al. Memetic improved cuckoo search algorithm for automatic B-spline border approximation of cutaneous melanoma from macroscopic medical images , 2020, Adv. Eng. Informatics.
[32] Nabil Derbel,et al. Melanoma Skin Cancer Detection based on Image Processing. , 2020, Current medical imaging reviews.
[33] P. C. Siddalingaswamy,et al. Techniques and algorithms for computer aided diagnosis of pigmented skin lesions - A review , 2018, Biomed. Signal Process. Control..
[34] Samy Bakheet,et al. An SVM Framework for Malignant Melanoma Detection Based on Optimized HOG Features , 2017, Comput..
[35] Adel Al-Jumaily,et al. Comparing the Performance of Various Filters on Skin Cancer Images , 2014 .
[36] Adel Al-Jumaily,et al. The Beneficial Techniques in Preprocessing Step of Skin Cancer Detection System Comparing , 2014 .
[37] G. Zouridakis,et al. Early diagnosis of skin cancer based on segmentation and measurement of vascularization and pigmentation in Nevoscope images , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[38] M S Woolfson,et al. Application of region-based segmentation and neural network edge detection to skin lesions. , 2004, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.
[39] Bülent Sankur,et al. Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.
[40] Clement T. Yu,et al. Segmentation of skin cancer images , 1999, Image Vis. Comput..
[41] Josef Kittler,et al. On threshold selection using clustering criteria , 1985, IEEE Transactions on Systems, Man, and Cybernetics.
[42] N. Otsu. A threshold selection method from gray level histograms , 1979 .