Authors
Bharadwaj, Kss
Pawar, Vivek
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Issue Date
2019
Publisher
University of Minnesota Libraries Publishing
Type
Article
Abstract
In this report,we have described an automated algorithm for accurate segmentation of kidney and kidney tumor from CT scans. The dataset for this problem was made available online as part of KiTS19 Challenge. Our model uses a 2 stage cascaded Residual Unet architecture. The first network is designed to predict (Kidney + Tumor) regions. The second network predicts segmented tumor regions from the output of first net. As a post processing step, we have designed a statistical metric which calculates the standard deviation of derivatives of centre of mass of predicted masks to filter out false positives.The report contains implementation details along with results on validation set.
Identifiers
doi: 10.24926/548719.047