Applications of artificial intelligence in the analysis of histopathology images of gliomas: a review

JP Redlich, F Feuerhake, J Weis, NS Schaadt… - npj Imaging, 2024 - nature.com
In recent years, the diagnosis of gliomas has become increasingly complex. Analysis of
glioma histopathology images using artificial intelligence (AI) offers new opportunities to …

Computational nuclei segmentation methods in digital pathology: a survey

T Hayakawa, VBS Prasath, H Kawanaka… - … Methods in Engineering, 2021 - Springer
Pathology is an important field in modern medicine. In particular, the step of nuclei
segmentation is an important step in cancer analysis, diagnosis, and grading because …

Automatic disease stage classification of glioblastoma multiforme histopathological images using deep convolutional neural network

A Yonekura, H Kawanaka, VBS Prasath… - Biomedical engineering …, 2018 - Springer
In the field of computational histopathology, computer-assisted diagnosis systems are
important in obtaining patient-specific diagnosis for various diseases and help precision …

Automatic cellularity assessment from post‐treated breast surgical specimens

M Peikari, S Salama, S Nofech‐Mozes… - Cytometry Part …, 2017 - Wiley Online Library
Neoadjuvant treatment (NAT) of breast cancer (BCa) is an option for patients with the locally
advanced disease. It has been compared with standard adjuvant therapy with the aim of …

NHL Pathological Image Classification Based on Hierarchical Local Information and GoogLeNet‐Based Representations

J Bai, H Jiang, S Li, X Ma - BioMed research international, 2019 - Wiley Online Library
Background. Accurate classification for different non‐Hodgkin lymphomas (NHL) is one of
the main challenges in clinical pathological diagnosis due to its intrinsic complexity …

A study on nuclei segmentation, feature extraction and disease stage classification for human brain histopathological images

K Fukuma, VBS Prasath, H Kawanaka… - Procedia Computer …, 2016 - Elsevier
Computer aided diagnosis (CAD) systems are important in obtaining precision medicine and
patient driven solutions for various diseases. One of the main brain tumor is the …

An efficient and effective model to handle missing data in classification

K Mehrabani-Zeinabad, M Doostfatemeh… - BioMed Research …, 2020 - Wiley Online Library
Missing data is one of the most important causes in reduction of classification accuracy.
Many real datasets suffer from missing values, especially in medical sciences. Imputation is …

Intelligent framework for brain tumor grading using advanced feature analysis

G Mohan - Computer Methods in Biomechanics and Biomedical …, 2023 - Taylor & Francis
The analysis of digital pathology images, catalyzes research and automate diagnosis for
improving clinical care. Regardless of the advances in high-resolution and speedy scanning …

Improving the generalization of disease stage classification with deep CNN for glioma histopathological images

A Yonekura, H Kawanaka, VBS Prasath… - 2017 IEEE …, 2017 - ieeexplore.ieee.org
In the field of histopathology, computer-assisted diagnosis systems are important in
obtaining patient-specific diagnosis for various diseases and help define precision …

Glioblastoma multiforme tissue histopathology images based disease stage classification with deep CNN

A Yonekura, H Kawanaka, VBS Prasath… - … and Vision & 2017 …, 2017 - ieeexplore.ieee.org
Recently, many feature extraction methods for histopathology images have been reported
for automatic quantitative analysis. One of the severe brain tumors is the Glioblastoma …