AI applications to medical images: From machine learning to deep learning.
By Isabella Castiglioni, Leonardo Rundo, M. Codari, G. Di Leo, C. Salvatore, M. Interlenghi, F. Gallivanone, A. Cozzi, N. D'Amico, Francesco Sardanelli. Physica medica (Testo stampato), 2021
612 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/3ad3cbad4b73e8f84707e7c686bcfda9e3421cf3
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In Artificial Intelligence
In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation (2021, background): “In recent years, however, significant progress has been achieved using deep learning (Ker et al., 2018; Rueckert and Schnabel, 2019; Castiglioni et al., 2021).”