%0 Conference Proceedings
%T Calcified Plaque Detection in IVUS Sequences: Preliminary Results Using Convolutional Nets
%A Simone Balocco
%A Mauricio Gonzalez
%A Ricardo Ñancule
%A Petia Radeva
%A Gabriel Thomas
%B International Workshop on Artificial Intelligence and Pattern Recognition
%D 2018
%V 11047
%F Simone Balocco2018
%O MILAB; no menciona
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3237), last updated on Tue, 22 Jan 2019 09:40:29 +0100
%X The manual inspection of intravascular ultrasound (IVUS) images to detect clinically relevant patterns is a difficult and laborious task performed routinely by physicians. In this paper, we present a framework based on convolutional nets for the quick selection of IVUS frames containing arterial calcification, a pattern whose detection plays a vital role in the diagnosis of atherosclerosis. Preliminary experiments on a dataset acquired from eighty patients show that convolutional architectures improve detections of a shallow classifier in terms of 𝐹1-measure, precision and recall.
%K Intravascular ultrasound images
%K Convolutional nets
%K Deep learning
%K Medical image analysis
%U https://link.springer.com/chapter/10.1007%2F978-3-030-01132-1_4
%P 34-42