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

Table_2_Differentiation between spinal multiple myeloma and metastases originated from lung using multi-view attention-guided network.docx

肿瘤影像鉴别诊断

医学影像深度学习

PurposeMultiple myeloma (MM) and metastasis originated are the two common malignancy diseases in the spine. They usually show similar imaging patterns and are highly demanded to differentiate for prec

NIAID Data Ecosystem40

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

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

[RSNA24]ALS-A-112-tf_efficientnet_b7-ch30-x512-lr

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