Computational normalization of H&E-stained histological images: Progress, challenges and future potential

TAA Tosta, PR de Faria, LA Neves… - Artificial intelligence in …, 2019 - Elsevier
Different types of cancer can be diagnosed with the analysis of histological samples stained
with hematoxylin–eosin (H&E). Through this stain, it is possible to identify the architecture of …

[HTML][HTML] What can machine vision do for lymphatic histopathology image analysis: a comprehensive review

H Chen, X Li, C Li, MM Rahaman, X Li, J Wu… - Artificial Intelligence …, 2024 - Springer
Over the past 10 years, machine vision (MV) algorithms for image analysis have been
developing rapidly with computing power. At the same time, histopathological slices can be …

Fractal Neural Network: A new ensemble of fractal geometry and convolutional neural networks for the classification of histology images

GF Roberto, A Lumini, LA Neves… - Expert Systems with …, 2021 - Elsevier
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 …

Classification of colorectal cancer based on the association of multidimensional and multiresolution features

MG Ribeiro, LA Neves, MZ do Nascimento… - Expert Systems with …, 2019 - Elsevier
Colorectal cancer is one of the most common types of cancer according to worldwide
incidences statistics. The correct diagnosis of this lesion leads to the indication of the most …

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 …

Classification of breast and colorectal tumors based on percolation of color normalized images

GF Roberto, MZ Nascimento, AS Martins, TAA Tosta… - Computers & …, 2019 - Elsevier
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 …

Selection of cnn, haralick and fractal features based on evolutionary algorithms for classification of histological images

D Candelero, GF Roberto… - 2020 IEEE …, 2020 - ieeexplore.ieee.org
The analysis of histological image features for automatic detection of pathologies plays an
important role in medicine. Considering that, we proposed a method based on the …

Lymphoma images analysis using morphological and non-morphological descriptors for classification

MZ do Nascimento, AS Martins, TAA Tosta… - Computer methods and …, 2018 - Elsevier
Mantle cell lymphoma, follicular lymphoma and chronic lymphocytic leukemia are the
principle subtypes of the non-Hodgkin lymphomas. The diversity of clinical presentations …

Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images

R Ferjaoui, MA Cherni, S Boujnah, NEH Kraiem… - Computer Methods and …, 2021 - Elsevier
Background: After the treatment of the patients with malignant lymphoma, there may persist
lesions that must be labeled either as evolutive lymphoma requiring new treatments or as …

[HTML][HTML] Classification of Multiple H&E Images via an Ensemble Computational Scheme

LHC Longo, GF Roberto, TAA Tosta, PR de Faria… - Entropy, 2023 - mdpi.com
In this work, a computational scheme is proposed to identify the main combinations of
handcrafted descriptors and deep-learned features capable of classifying histological …