Multi-decoder Networks with Multi-denoising Inputs for Tumor Segmentation

Author:

Vu Minh H.,Nyholm Tufve,Löfstedt Tommy

Publisher

Springer International Publishing

Reference21 articles.

1. Ali, H.M.: A new method to remove salt pepper noise in magnetic resonance images. In: 2016 11th International Conference on Computer Engineering Systems (ICCES), pp. 155–160 (2016)

2. Bakas, S., et al.: Segmentation labels and radiomic features for the pre-operative scans of the TCGA-GBM collection. The cancer imaging archive (2017) (2017)

3. Bakas, S., et al.: Segmentation labels and radiomic features for the pre-operative scans of the TCGA-LGG collection. Cancer Imaging Archive 286 (2017)

4. Bakas, S., et al.: Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features. Sci. Data 4, 170117 (2017)

5. Bakas, S., et al.: Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge. arXiv preprint arXiv:1811.02629 (2018)

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