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Found 4 papers, 1 papers with code
MultiNet with Transformers: A Model for Cancer Diagnosis Using Images
Cancer is a leading cause of death in many countries.
Multiclass Semantic Segmentation to Identify Anatomical Sub-Regions of Brain and Measure Neuronal Health in Parkinson's Disease
Automated segmentation of anatomical sub-regions with high precision has become a necessity to enable the quantification and characterization of cells/ tissues in histology images.
A Deep Learning Study on Osteosarcoma Detection from Histological Images
In this study, transfer learning techniques, pre-trained CNNs, are adapted to a public dataset on osteosarcoma histological images to detect necrotic images from non-necrotic and healthy tissues.
C-Net: A Reliable Convolutional Neural Network for Biomedical Image Classification
In this study, we propose a novel convolutional neural network (CNN) architecture composed of a Concatenation of multiple Networks, called C-Net, to classify biomedical images.
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