학술논문

Stroke Thrombus Segmentation on SWAN with Multi-Directional U-Nets
Document Type
Conference
Source
2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA) Image Processing Theory, Tools and Applications (IPTA), 2019 Ninth International Conference on. :1-6 Nov, 2019
Subject
Computing and Processing
Signal Processing and Analysis
Magnetic resonance imaging
Image segmentation
Task analysis
Histograms
Training
Magnetic susceptibility
Brain
Stroke
Thrombus
Deep Learning
MRI
Automatic Segmentation.
Language
ISSN
2154-512X
Abstract
The thrombus causing a stroke can be seen on the susceptibility weighted angiography (SWAN) magnetic resonance imaging (MRI) sequence. But it is very small and hard to detect by humans. Up to date the thrombus is identified by trained human experts. But as stroke needs quick treatment, an automatic detection of the thrombus would be useful to speed up the diagnosis of acute stroke. We propose a method for automatic thrombus detection from SWAN using three separate U-Nets which work on the axial, coronal and sagittal planes.