Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks

Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks

In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed system is based on a lightweight deep neural network architecture composed of a convolutional neural network (CNN) that takes as in...

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Bibliographic Details
Main Authors: Mihail Burduja, Radu Tudor Ionescu, Nicolae Verga
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Sensors
Subjects:
intracranial hemorrhage detection
intracranial hemorrhage subtype classification
convolutional neural networks
long short-term memory networks
Online Access:https://www.mdpi.com/1424-8220/20/19/5611

Internet

https://www.mdpi.com/1424-8220/20/19/5611

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