A multimodal auxiliary classification system for osteosarcoma histopathological images based on deep active learning
F Gou, J Liu, J Zhu, J Wu - Healthcare, 2022 - mdpi.com
Histopathological examination is an important criterion in the clinical diagnosis of
osteosarcoma. With the improvement of hardware technology and computing power …
osteosarcoma. With the improvement of hardware technology and computing power …
A novel hybrid approach for classifying osteosarcoma using deep feature extraction and multilayer perceptron
Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and
young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise …
young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise …
A deep learning study on osteosarcoma detection from histological images
Abstract In the US 5–10% of new pediatric cases of cancer are primary bone tumors. The
most common type of primary malignant bone tumor is osteosarcoma. The intention of the …
most common type of primary malignant bone tumor is osteosarcoma. The intention of the …
Adapted Deep Ensemble Learning-Based Voting Classifier for Osteosarcoma Cancer Classification
The study utilizes osteosarcoma hematoxylin and the Eosin-stained image dataset, which is
unevenly dispersed, and it raises concerns about the potential impact on the overall …
unevenly dispersed, and it raises concerns about the potential impact on the overall …
Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models
HB Arunachalam, R Mishra, O Daescu, K Cederberg… - PloS one, 2019 - journals.plos.org
Pathological estimation of tumor necrosis after chemotherapy is essential for patients with
osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic …
osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic …
Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma
The degree of malignancy of osteosarcoma and its tendency to metastasize/spread mainly
depend on the pathological grade (determined by observing the morphology of the tumor …
depend on the pathological grade (determined by observing the morphology of the tumor …
Deep Learning Approaches to Osteosarcoma Diagnosis and Classification: A Comparative Methodological Approach
Simple Summary Osteosarcoma is a rare form of bone cancer that primarily affects children
and adolescents during their growth years. Known to be one of the most aggressive tumors …
and adolescents during their growth years. Known to be one of the most aggressive tumors …
IoMT-based osteosarcoma cancer detection in histopathology images using transfer learning empowered with blockchain, fog computing, and edge computing
Bone tumors, such as osteosarcomas, can occur anywhere in the bones, though they
usually occur in the extremities of long bones near metaphyseal growth plates …
usually occur in the extremities of long bones near metaphyseal growth plates …
Histopathological diagnosis for viable and non-viable tumor prediction for osteosarcoma using convolutional neural network
Pathologists often deal with high complexity and sometimes disagreement over
Osteosarcoma tumor classification due to cellular heterogeneity in the dataset …
Osteosarcoma tumor classification due to cellular heterogeneity in the dataset …
Deep model with Siamese network for viable and necrotic tumor regions assessment in osteosarcoma
Purpose To achieve automatic classification of viable and necrotic tumor regions in
osteosarcoma, most of the existing deep learning methods can only design a simple model …
osteosarcoma, most of the existing deep learning methods can only design a simple model …