FPGA implementation of deep learning architecture for kidney cancer detection from histopathological images
Kidney cancer is the most common type of cancer, and designing an automated system to
accurately classify the cancer grade is of paramount importance for a better prognosis of the …
accurately classify the cancer grade is of paramount importance for a better prognosis of the …
MPSA: Multi-Position Supervised Soft Attention-based convolutional neural network for histopathological image classification
B Qing, S Zhanquan, W Kang, W Chaoli… - Expert Systems with …, 2024 - Elsevier
In recent years, significant achievements have been made in the field of histopathological
image analysis using convolutional neural networks (CNNs). However, existing CNNs fail to …
image analysis using convolutional neural networks (CNNs). However, existing CNNs fail to …
Classification and grade prediction of kidney cancer histological images using deep learning
Abstract Renal Cell Carcinoma (RCC) is the most common malignant tumor (85%) of kidney
cancer and has a complex histological pattern and nuclear structure. The manual diagnosis …
cancer and has a complex histological pattern and nuclear structure. The manual diagnosis …
A novel Nine-SequenceNet with attention for liver histopathological classification
L Sun, Z Sun, C Wang, S Cheng, K Wang - Biomedical Signal Processing …, 2024 - Elsevier
Liver cancer is a prevalent cancer worldwide and is also the leading cause of cancer-related
deaths. Histopathological image diagnosis is taken as the standard to identify liver cancer …
deaths. Histopathological image diagnosis is taken as the standard to identify liver cancer …
Breast Cancer Classification through Meta-Learning Ensemble Model based on Deep Neural Networks
S Padmini P, KA Kumar, K Chanthirasekaran… - Journal of Information …, 2024 - jitm.ut.ac.ir
Predicting the development of cancer has always been a serious challenge for scientists
and medical professionals. The prompt identification and prognosis of a disease is greatly …
and medical professionals. The prompt identification and prognosis of a disease is greatly …