Texture analysis and its applications in biomedical imaging: A survey
MK Ghalati, A Nunes, H Ferreira… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
Texture analysis describes a variety of image analysis techniques that quantify the variation
in intensity and pattern. This paper provides an overview of several texture analysis …
in intensity and pattern. This paper provides an overview of several texture analysis …
EntropyHub: An open-source toolkit for entropic time series analysis
An increasing number of studies across many research fields from biomedical engineering
to finance are employing measures of entropy to quantify the regularity, variability or …
to finance are employing measures of entropy to quantify the regularity, variability or …
Multiscale permutation entropy for two-dimensional patterns
C Morel, A Humeau-Heurtier - Pattern Recognition Letters, 2021 - Elsevier
Complexity measures are important to understand and analyze systems with one
dimensional data. However, extension of these methods to images (two dimensional data) …
dimensional data. However, extension of these methods to images (two dimensional data) …
Fractal Neural Network: A new ensemble of fractal geometry and convolutional neural networks for the classification of histology images
Classification of histology images is a task that has been widely explored on recent
computer vision researches. The most studied approach for this task has been the …
computer vision researches. The most studied approach for this task has been the …
Hybrid models for classifying histological images: An association of deep features by transfer learning with ensemble classifier
The use of a convolutional neural network with transfer learning is a strategy that defines
high-level features, commonly explored to study patterns in medical images. These features …
high-level features, commonly explored to study patterns in medical images. These features …
Classification of non-Hodgkin lymphomas based on sample entropy signatures
Computational systems to provide studies and diagnoses of non-Hodgkin's lymphomas
have been increasingly developed to assist specialists in their decision-making. On the …
have been increasingly developed to assist specialists in their decision-making. On the …
Histological image classification using deep features and transfer learning
S Alinsaif, J Lang - 2020 17th Conference on Computer and …, 2020 - ieeexplore.ieee.org
A major challenge in the automatic classification of histopathological images is the limited
amount of data available. Supervised learning techniques cannot be applied without some …
amount of data available. Supervised learning techniques cannot be applied without some …
Differentiation of Alzheimer conditions in brain MR images using bidimensional multiscale entropy-based texture analysis of lateral ventricles
A Veluppal - Biomedical Signal Processing and Control, 2022 - Elsevier
Alzheimer's Disease (AD) is a progressive fatal neurodegenerative disorder that causes
cognitive decline in affected people. Image processing of brain MR images can aid in …
cognitive decline in affected people. Image processing of brain MR images can aid in …
The novel approach of temporal dependency complexity analysis of heart rate variability in obstructive sleep apnea
L Tang, G Liu - Computers in Biology and Medicine, 2021 - Elsevier
Obstructive sleep apnea (OSA) is a serious sleep disorder, which leads to changes in
autonomic nerve function and increases the risk of cardiovascular disease. Heart rate …
autonomic nerve function and increases the risk of cardiovascular disease. Heart rate …
Classification of breast and colorectal tumors based on percolation of color normalized images
Percolation is a fractal descriptor that has been applied recently on computer vision
problems. We applied this descriptor on 58 colored histological breast images, and 165 …
problems. We applied this descriptor on 58 colored histological breast images, and 165 …