Segmentation of corpus callosum in midsagittal plane using convolutional neural networks with anatomical information

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초록

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 InformationConvolutional Neural NetworksCorpus CallosumSegmentationBrainConvolutionImage segmentationNeural networksAnatomical informationConvolutional neural networkCorpus callosumMid-sagittal planesNeurological diseaseRobust segmentationSegmentation performanceStructural featureComputer vision
제목
Segmentation of corpus callosum in midsagittal plane using convolutional neural networks with anatomical information
저자
Park, GilsoonLee, 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