Distribution of breast NMLs with different ultrasound features.
收藏NIAID Data Ecosystem2026-03-14 收录
数据链接：
官方服务：
资源简介：
Distribution of breast NMLs with different ultrasound features.
应用场景：
创建时间：
2022-11-30
相关数据集
Data from: Computational pathology to discriminate benign from malignant intraductal proliferations of the breast
The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced path
DataONE2014-12-10 更新140
Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions
We uploaded the 15 morphological features of 91 samples of 85 patients analyzed in the manuscript: Fusco, Roberta, Adele Piccirillo, Mario Sansone, Vincenza Granata, Paolo Vallone, Maria L. Barretta,
NIAID Data Ecosystem40
Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification.
We uploaded the database of 104 lesions included in the manuscript: Fusco R, Piccirillo A, Sansone M, Granata V, Rubulotta MR, Petrosino T, Barretta ML, Vallone P, Di Giacomo R, Esposito E, Di Bonito
NIAID Data Ecosystem30
DataSheet_1_A deep learning model based on dynamic contrast-enhanced magnetic resonance imaging enables accurate prediction of benign and malignant breast lessons.docx
ObjectivesThe study aims to investigate the value of a convolutional neural network (CNN) based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting malignancy of breast les
NIAID Data Ecosystem50
Data_Sheet_1_Radiomic Analysis of Contrast-Enhanced Mammography With Different Image Types: Classification of Breast Lesions.docx
Objective: A limited number of studies have focused on the radiomic analysis of contrast-enhanced mammography (CEM). We aimed to construct several radiomics-based models of CEM for classifying benign
NIAID Data Ecosystem30
