Spatial information using CRF for brain tumor segmentation

Yawen Chen*, Sei Ichiro Kamata, Rong Fan

*この研究の対応する著者

研究成果: Conference contribution

抄録

In this work, we proposed a method combined the fuzzy spatial correlation of voxels in the MRI images obtained from a 3D network using CRF with the slice information captured by an ordinary 2D network to focus on the brain tumor segmentation task. Considering the expensive devices required by 3D networks while 2D networks can loss the information in the channel direction which leads to many false positive predictions, the proposed one can be a favorable direction to get more accurate features of the brain tumor. We take MRI images with 4 modalities in BRATS2018 dataset as the input of the 3D CNN after reducing the resolution. The CRF is used to calculate the neighboring correlation after the CNN feature extractor and can generate the probability map. The 2D network takes 2D slices in 4 modalities from the MRI images as input and output the segmentation map. The 2D segmentation maps are joining to 3D in order and combined with the probability map to get the final result. Compared with the state-of-the-art and the baseline method with the average Dice less than 0.85, the proposed is time and memory saving with the average Dice nearly 0.88.

本文言語English
ホスト出版物のタイトルThirteenth International Conference on Digital Image Processing, ICDIP 2021
編集者Xudong Jiang, Hiroshi Fujita
出版社SPIE
ISBN(電子版)9781510646001
DOI
出版ステータスPublished - 2021
イベント13th International Conference on Digital Image Processing, ICDIP 2021 - Singapore, Singapore
継続期間: 2021 5 202021 5 23

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
11878
ISSN(印刷版)0277-786X
ISSN(電子版)1996-756X

Conference

Conference13th International Conference on Digital Image Processing, ICDIP 2021
国/地域Singapore
CitySingapore
Period21/5/2021/5/23

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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