What is it about?
In this a new learning or training hybrid approach is proposed based on the Google's inception module and a U-Net topology and a segmentation loss function based on Jaccard index, dice coefficient and binary cross entropy metrics
Photo by Hitesh Choudhary on Unsplash
Why is it important?
Nuclei are the first things that gets affected during illness or disease. The automated detection of nuclei can help the doctors in faster diagnosis and treatment of the illness.
Read the Original
This page is a summary of: Inception U-Net Architecture for Semantic Segmentation to Identify Nuclei in Microscopy Cell Images, ACM Transactions on Multimedia Computing Communications and Applications, April 2020, ACM (Association for Computing Machinery), DOI: 10.1145/3376922.
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