Sep 10, 2021 · In this work, we propose an end-to-end MB tumor classification and explore transfer learning with various input sizes and matching network ...

For this purpose, we systematically evaluate recently proposed Effi-. cientNets, which uniformly scale all dimensions of a CNN. Using a data set with 161 cases, ...

This work proposes an end-to-end MB tumor classification and explores transfer learning with various input sizes and matching network dimensions and ...

Sep 10, 2021 · For this purpose, we systematically evaluate recently proposed Effi-. cientNets, which uniformly scale all dimensions of a CNN. Using a data set ...

Sep 8, 2024 · In this work, we propose an end-to-end MB tumor classification and explore transfer learning with various input sizes and matching network ...

In these analyses, WSI were used to extract key features to develop and train machine and deep learning models for the prediction of histologic subtypes of ...

Aug 27, 2021 · We study the impact of tile size and input strategy and classify the two major histopathological subtypes-Classic and Desmoplastic/Nodular. To ...

Medulloblastoma tumor classification using deep transfer learning with multi-scale EfficientNets · Advanced Deep Convolutional Neural Network Approaches for ...

Multi-Scale Input Strategies for Medulloblastoma Tumor Classification using Deep Transfer Learning ... EfficientNets and evaluate tiles with increasing size ...

Medulloblastoma Tumor Classification using Deep Transfer. Learning with Multi-Scale EfficientNets. In Medical Imaging. 2021: Digital Pathology, volume 11603 ...