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 …
Multidimensional and fuzzy sample entropy (SampEnMF) for quantifying H&E histological images of colorectal cancer
LFS Dos Santos, LA Neves, GB Rozendo… - Computers in biology …, 2018 - Elsevier
In this study, we propose to use a method based on the combination of sample entropy with
multiscale and multidimensional approaches, along with a fuzzy function. The model was …
multiscale and multidimensional approaches, along with a fuzzy function. The model was …
Features based on the percolation theory for quantification of non-hodgkin lymphomas
Non-Hodgkin lymphomas are a health problem that affects over 70,000 people per year in
the United States alone. The early diagnosis and the identification of this lymphoma are …
the United States alone. The early diagnosis and the identification of this lymphoma are …
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 …
[HTML][HTML] Exploring percolation features with polynomial algorithms for classifying Covid-19 in chest X-ray images
Covid-19 is a severe illness caused by the Sars-CoV-2 virus, initially identified in China in
late 2019 and swiftly spreading globally. Since the virus primarily impacts the lungs …
late 2019 and swiftly spreading globally. Since the virus primarily impacts the lungs …
JCLMM: A finite mixture model for clustering of circular-linear data and its application to psoriatic plaque segmentation
The hue and chroma components of an image pixel carry crucial information that can be
exploited to perform segmentation. However, due to its directional property, a circular …
exploited to perform segmentation. However, due to its directional property, a circular …
Classification of Multiple H&E Images via an Ensemble Computational Scheme
In this work, a computational scheme is proposed to identify the main combinations of
handcrafted descriptors and deep-learned features capable of classifying histological …
handcrafted descriptors and deep-learned features capable of classifying histological …
Analysis of cancer in histological images: employing an approach based on genetic algorithm
DF Taino, MG Ribeiro, GF Roberto… - Pattern Analysis and …, 2021 - Springer
The analysis of histological images is based on visual assessment of tissues by specialists
using an optical microscopy. This task can be time-consuming and challenging, mainly due …
using an optical microscopy. This task can be time-consuming and challenging, mainly due …
A hermite polynomial algorithm for detection of lesions in lymphoma images
There are different types of lesions that can be investigated with the hematoxylin–eosin
staining protocol. Lymphoma is a type of malignant disease which affects one of the highest …
staining protocol. Lymphoma is a type of malignant disease which affects one of the highest …
An ensemble of learned features and reshaping of fractal geometry-based descriptors for classification of histological images
Classification of histology images has been the focus of plenty researchers in computer
vision. Recently, the most common approaches for this task consist of applying deep …
vision. Recently, the most common approaches for this task consist of applying deep …