Deep-learning algorithm to detect anomalies in compressed breast: A numerical study

Ganesh M. Balasubramaniam, Shlomi Arnon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationBio-Optics
Subtitle of host publicationDesign and Application, BODA 2021
PublisherThe Optical Society
ISBN (Electronic)9781557528209
StatePublished - 1 Jan 2021
EventBio-Optics: Design and Application, BODA 2021 - Part of Biophotonics Congress: Optics in the Life Sciences 2021 - Virtual, Online, United States
Duration: 12 Apr 202116 Apr 2021

Publication series

NameOptics InfoBase Conference Papers

Conference

ConferenceBio-Optics: Design and Application, BODA 2021 - Part of Biophotonics Congress: Optics in the Life Sciences 2021
Country/TerritoryUnited States
CityVirtual, Online
Period12/04/2116/04/21

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