Leukemia diagnosis in blood slides using transfer learning in CNNs and SVM for classification
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Romuere Rôdrigues Veloso e Silva | Kelson Rômulo Teixeira Aires | Rodrigo M. S. Veras | Flávio H. D. Araújo | Luis H. S. Vogado | Romuere R. V. Silva | R. Veras | L. Vogado | K. Aires | L. H. Vogado
[1] Nauman Aslam,et al. An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images , 2015, Scientific Reports.
[2] Hossein Rabbani,et al. Detecting different sub-types of acute myelogenous leukemia using dictionary learning and sparse representation , 2015, 2015 IEEE International Conference on Image Processing (ICIP).
[3] Alex Pentland,et al. Fractal-Based Description of Natural Scenes , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Ki-Ryong Kwon,et al. Acute lymphoid leukemia classification using two-step neural network classifier , 2015, 2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV).
[5] Isabelle Guyon,et al. An Introduction to Feature Extraction , 2006, Feature Extraction.
[6] Ronald M. Summers,et al. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning , 2016, IEEE Transactions on Medical Imaging.
[7] Nikos E. Mastorakis,et al. Multilayer perceptron and neural networks , 2009 .
[8] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[9] Cecilia Di Ruberto,et al. Leucocyte classification for leukaemia detection using image processing techniques , 2014, Artif. Intell. Medicine.
[10] Hossein Rabbani,et al. Selection of the best features for leukocytes classification in blood smear microscopic images , 2014, Medical Imaging.
[11] Sos S. Agaian,et al. A new acute leukaemia-automated classification system , 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..
[12] Ian H. Witten,et al. The WEKA data mining software: an update , 2009, SKDD.
[13] Vanika Singhal,et al. Texture Features for the Detection of Acute Lymphoblastic Leukemia , 2016 .
[14] Nima Tajbakhsh,et al. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? , 2016, IEEE Transactions on Medical Imaging.
[15] Alireza Mehri Dehnavi,et al. Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing , 2015, Advanced biomedical research.
[16] Ashutosh Mishra,et al. Automated Leukaemia Detection Using Microscopic Images , 2015 .
[17] Friedhelm Schwenker,et al. Three learning phases for radial-basis-function networks , 2001, Neural Networks.
[18] David M. W. Powers,et al. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation , 2011, ArXiv.
[19] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[20] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[21] Jay S. Raval,et al. Experience with CellaVision DM96 for peripheral blood differentials in a large multi-center academic hospital system , 2012, Journal of pathology informatics.
[22] David Dagan Feng,et al. An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification , 2017, IEEE Journal of Biomedical and Health Informatics.
[23] Dipti Patra,et al. An ensemble classifier system for early diagnosis of acute lymphoblastic leukemia in blood microscopic images , 2013, Neural Computing and Applications.
[24] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[25] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[26] Nir Friedman,et al. Bayesian Network Classifiers , 1997, Machine Learning.
[27] Dong-Chen He,et al. Texture Unit, Texture Spectrum, And Texture Analysis , 1990 .
[28] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[29] David W. Aha,et al. Instance-Based Learning Algorithms , 1991, Machine Learning.