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Segmentation of corpus callosum in midsagittal plane using convolutional neural networks with anatomical information
- Park, Gilsoon;
- Lee, Jong Min
Citations
SCOPUS
0초록
Corpus Callosum (CC), the largest white matter structure, is connector between the two cerebral hemispheres in human brain. Structural features of CC such as shape and size have been used to study various neurological diseases. Robust segmentation of CC in midsagittal plane is critical in the qualitative studies. In this paper, we introduced a convolutional neural networks (CNN) with anatomical information for CC segmentation. Our method showed better segmentation performance (mean Dice index: 95.44±0.9859) than other methods (mean Dice index: 95.22±1.2532). We concluded that anatomical information integrated in CNN improve the segmentation performance significantly.
키워드
Anatomical Information; Convolutional Neural Networks; Corpus Callosum; Segmentation; Brain; Convolution; Image segmentation; Neural networks; Anatomical information; Convolutional neural network; Corpus callosum; Mid-sagittal planes; Neurological disease; Robust segmentation; Segmentation performance; Structural feature; Computer vision
- 제목
- Segmentation of corpus callosum in midsagittal plane using convolutional neural networks with anatomical information
- 저자
- Park, Gilsoon; Lee, Jong Min
- 발행일
- 2017-07
- 유형
- Conference Paper
- 저널명
- Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017
- 페이지
- 141 ~ 142
- 언어
- ENG
- 출판사
- CSREA Press
- 발행국가
- 영국
- 분량
- 2 페이지
- ISSN
- P 0000-0000