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Abstract #0852

Brain Tumor Segmentation Using 3D CMM-Net with Limited and Accessible MR Images

Yoonseok Choi1, Mohammed A. Al-masni1, and Dong-Hyun Kim1
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of


In this work, we investigate the possibility of using a limited number of medical MR images for brain tumor segmentation. This can assist to perform the segmentation task using limited and accessible data in clinical practice. We observed that the FLAIR and T1CE are the most suitable images that maintain comparable segmentation performances similar to the case of using more data (i.e., T1, T2, FLAIR, and T1CE). To further improve the segmentation results, we augment the selected image pair and generate an additional fusion map using the Singular Value Decomposition (SVD).

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