Tumor delineation from 3-D MR brain images

Author:

Roy Shaswati,Maji Pradipta

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Reference30 articles.

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

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

4. Bal, A., Banerjee, M., Chakrabarti, A., et al.: MRI brain tumor segmentation and analysis using rough-fuzzy c-means and shape based properties. J. King Saud Univ. Comput. Inf. Sci. 34(2), 115–133 (2022)

5. Banerjee, A., Maji, P.: Rough sets and stomped normal distribution for simultaneous segmentation and bias field correction in brain MR images. IEEE Trans. Image Process. 24(12), 5764–5776 (2015)

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