A Statistical Approach to Assess the Robustness of Radiomics Features in the Discrimination of Mammographic Lesions
Despite mammography (MG) being among the most widespread techniques in breast cancer screening, tumour detection and classification remain challenging tasks due to the high morphological variability of the lesions. The extraction of radiomics features has proved to be a promising approach in MG. How...
Main Authors: | Alfonso Maria Ponsiglione, Francesca Angelone, Francesco Amato, Mario Sansone |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | Journal of Personalized Medicine |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-4426/13/7/1104 |
Similar Items
-
Contrast-Enhanced Spectral Mammography-Based Radiomics Nomogram for Identifying Benign and Malignant Breast Lesions of Sub-1 cm
by: Fan Lin, et al.
Published: (2020-10-01) -
Incorporating Robustness to Imaging Physics into Radiomic Feature Selection for Breast Cancer Risk Estimation
by: Raymond J. Acciavatti, et al.
Published: (2021-11-01) -
Machine Learning Approaches with Textural Features to Calculate Breast Density on Mammography
by: Mario Sansone, et al.
Published: (2023-01-01) -
Radiomic Analysis of Contrast-Enhanced Mammography With Different Image Types: Classification of Breast Lesions
by: Simin Wang, et al.
Published: (2021-05-01) -
Loss of Mammographic Tissue Homeostasis in Invasive Lobular and Ductal Breast Carcinomas vs. Benign Lesions
by: Evgeniya Gerasimova-Chechkina, et al.
Published: (2021-05-01)