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, Teresa Petrosino, Claudio Siani, Raimondo Di Giacomo, Maurizio Di Bonito, Gerardo Botti, and Antonella Petrillo. 2021. "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" Applied Sciences 11, no. 4: 1880. https://doi.org/10.3390/app11041880本数据集上传了本论文分析的85名患者的91份样本的15项形态学特征。相关学术文献信息如下：作者团队包括Fusco, Roberta、Adele Piccirillo、Mario Sansone、Vincenza Granata、Paolo Vallone、Maria L. Barretta、Teresa Petrosino、Claudio Siani、Raimondo Di Giacomo、Maurizio Di Bonito、Gerardo Botti、Antonella Petrillo；该研究于2021年发表于《Applied Sciences》（《应用科学》），文章标题为"利用动态对比增强磁共振成像（Dynamic Contrast-Enhanced Magnetic Resonance Imaging）提取的纹理指标、形态学及动态灌注特征开展乳腺病变分类的放射组学与人工智能分析"，刊载于第11卷第4期，页码为1880，DOI链接：https://doi.org/10.3390/app11041880