Prof. Shlomi Arnon
Deep-learning algorithm to detect anomalies in compressed breast
A numerical study
A deep-learning algorithm is employed to detect simulated anomalies inside compressed breasts using near-infrared light. Anomaly detection is improved by 55% after employing the algorithm according to the Dice similarity coefficient.
| Publication language | English |
| Publication status | Published - 01.01.2021 |
ASJC Scopus subject areas
Electronic, Optical and Magnetic Materials
Mechanics of Materials
