官方服务：
资源简介：
DINOの事前学習の重み 全国医療愛コンテスト2022
应用场景：
创建时间：
2022-03-22
相关数据集
patches and local annotations, slide 142, zoom 124x124 um2
patches and local annotations: data for slide with ID of the last 3 characters of the file name: local annotations in csv format and a folder with patches at zoom level indicated at the 6th character
DataCite Commons2022-06-24 更新50
patches and local annotations, slide 176, zoom 248x248 um2
patches and local annotations: data for slide with ID of the last 3 characters of the file name: local annotations in csv format and a folder with patches at zoom level indicated at the 6th character
DataCite Commons2022-06-24 更新50
Heatmap results of the Asan test dataset
1) We created heatmap figures by using a python Grad-CAM. ( https://github.com/gcucurull/CAM-Python ) 2)/heatmap_fig2The heatmap result of the case of malignant melanoma and basal cell carcinoma. (Fig
NIAID Data Ecosystem40
patches and local annotations, slide 159, zoom 248x248 um2
patches and local annotations: data for slide with ID of the last 3 characters of the file name: local annotations in csv format and a folder with patches at zoom level indicated at the 6th character
DataCite Commons2022-06-24 更新50
Data_Sheet_2_Supervised Machine-Learning Enables Segmentation and Evaluation of Heterogeneous Post-treatment Changes in Multi-Parametric MRI of Soft-Tissue Sarcoma.PDF
Background: Multi-parametric MRI provides non-invasive methods for response assessment of soft-tissue sarcoma (STS) from non-surgical treatments. However, evaluation of MRI parameters over the whole t
NIAID Data Ecosystem40
