Kidney and tumor segmentation using combined Deep learning method
Yuliia Kamkova, Hemin Ali Qadir, Ole Jakob, Rahul Prasanna Kumar · 2019
This paper presents our method for automatic segmentation for kidney and tumor as part of the Kidney Tumor Segmentation Challenge (KiTS19).The KiTS19 Challenge had released a dataset of 300 unique kidney cancer patients, with manual annotations done by Climb 4 Kidney Cancer (C4KC).Here we have proposed our new combined cascade deep learning (DL) approach for solving the tasks of the challenge.We used deep learning based detection for localising kidney with the tumor, followed by deep learning based segmentation to create the labels for kidney and tumor locally.Our approach resulted in high recall (96.13) and high Jacquard score (95.4) on the randomly selected 30 volumes that were picked as the validation set.