Multichannel DenseNet Architecture for Classification of Mammographic Breast Density for Breast Cancer Detection

• Published in: Frontiers in public health Vol. 10; p. 885212
• Main Authors: Pawar, Shivaji D, Sharma, Kamal K, Sapate, Suhas G, Yadav, Geetanjali Y, Alroobaea, Roobaea, Alzahrani, Sabah M, Hedabou, Mustapha
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 25.04.2022
• Subjects: Artificial Intelligence; BIRADS Density Classification; breast cancer; Breast Density; Breast Neoplasms - diagnostic imaging; deep learning; DenseNet; Female; Humans; mammographic breast density; Mammography - methods; multichannel architecture; Neural Networks, Computer; Public Health; DenseNet; deep learning; breast cancer; BIRADS Density Classification; multichannel architecture; mammographic breast density

Percentage mammographic breast density (MBD) is one of the most notable biomarkers. It is assessed visually with the support of radiologists with the four qualitative Breast Imaging Reporting and Data System (BIRADS) categories. It is demanding for radiologists to differentiate between the two varia...