Actas de congresos
Denoising digital breast tomosynthesis projections using convolutional neural networks
Fecha
2021-01-01Registro en:
Progress in Biomedical Optics and Imaging - Proceedings of SPIE, v. 11596.
1605-7422
10.1117/12.2582185
2-s2.0-85103639916
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
The Digital Breast Tomosynthesis (DBT) projections are obtained with low quality, being essential to use denoising methods to increase the quality of the projections. Currently, deep learning methods have become the state-of-art approach in denoising. Some papers have proposed to apply deep learning methods for denoising DBT projections, however, there is a lack of clarity in the results comparing with traditional methods. In this paper, we proposed to use a CNN to denoise DBT projections, and compare it with traditional denoising methods. The results shown that the CNN is superior quantitatively and qualitatively in comparison with the traditional methods.