This dataset contains the Supporting data for "Data-efficient Ultrasound Imaging Analysis with Deep Learning". These studies emphasize the importance and demonstrate the feasibility of achieving high

DataCite Commons2023-12-14 更新70

Harnessing clinical annotations to improve deep learning performance in prostate segmentation

前列腺研究

医学影像深度学习

Purpose Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the

NIAID Data Ecosystem50

Data_Sheet_1_A Reparametrized CNN Model to Distinguish Alzheimer's Disease Applying Multiple Morphological Metrics and Deep Semantic Features From Structural MRI.pdf

阿尔茨海默病影像识别

医学影像深度学习

It is of potential clinical value to improve the accuracy of Alzheimer's disease (AD) recognition using structural MRI. We proposed a reparametrized convolutional neural network (Re-CNN) to discrimina

NIAID Data Ecosystem70

Supplementary Table S1-S3 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group

分子亚型预测

医学影像深度学习

Supplemental Table S1. Whole slide image tissue segmentation statistics by an expert pathologist and probability prediction using a trained convolutional neural network. Supplemental Table S2. Clinica

NIAID Data Ecosystem60