U-Net Variations for Spontaneous Intracranial Hemorrhages Detection on CT Images
Author:
Affiliation:
1. Universidad San Francisco de Quito USFQ,Colegio de Ciencias e Ingenierías "El Politécnico",Quito,Ecuador,170157
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9904950/9905075/09905370.pdf?arnumber=9905370
Reference21 articles.
1. Towards effective classification of brain hemorrhagic and ischemic stroke using CNN
2. Segmentation of ischemic stroke area from CT brain images
3. Deep network for the automatic segmentation and quantification of intracranial hemorrhage on ct;xu;Frontiers in Neuroscience,2021
4. A Robust Deep Learning Segmentation Method for Hematoma Volumetric Detection in Intracerebral Hemorrhage
5. Detecting Intracranial Hemorrhage with Deep Learning
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1. Extending the U-Net Architecture for Strokes Segmentation on CT Scan Images;2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS);2023-07-04
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