A deep learning methodology for fully-automated quantification of calcific burden in high-resolution intravascular ultrasound images

Exploring foci of: doi.org A deep learning methodology for fully-automated quantification of calcific burden in high-resolution intravascular ultrasound images September 2025 • Xingwei He, Mohamed O. Mohamed, Nicole Ng, Thamil Kumaran, Retesh Bajaj, Nathan Angelo Lecaros Yap, Emrah Erdoğan, Mehmet Eren, Anthony Mathur, Ahmet… <title>Abstract</title> Purpose Quantification of the calcific burden is valuable in percutaneous coronary intervention (PCI) planning and in research to assess its changes after pharmacotherapies targeting plaque progression. In intravascular ultrasound (IVUS) images this analysis is currently performed manually and time consuming. To overcome these limitations, we introduce a deep-learning (DL) method for seamless detection of the calcific tissue Methods IVUS images from 197 vessels were analysed by an expert wh… Open Article Page

Learning Curve Learning Theory (Education) Experiential Learning Practice (Learning Method) Deep Purple Deep Water (2022 Film) Still Wakes The Deep Learning Environment Machine Learning Open Article

Deep Throat (Film) 5S (Methodology) Challenger Deep Deep Impact (Film) Deep Vein Thrombosis Mobb Deep Deep Web Deep South Deep Learning Open Article

Reinforcement Learning Deep Blue Sea (1999 Film) The Deep End Of The Ocean (Film) Deep Throat (Watergate) Learning Standards The Deep (1977 Film) Open Article