Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

Volume: 41, Issue: 1, Pages: 176 - 189
Published: Jan 1, 2019
Abstract
Robust and fast detection of anatomical structures is a prerequisite for both diagnostic and interventional medical image analysis. Current solutions for anatomy detection are typically based on machine learning techniques that exploit large annotated image databases in order to learn the appearance of the captured anatomy. These solutions are subject to several limitations, including the use of suboptimal feature engineering techniques and most...
Paper Details
Title
Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans
Published Date
Jan 1, 2019
Volume
41
Issue
1
Pages
176 - 189
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.