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A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery
2017
PLoS ONE
Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image
doi:10.1371/journal.pone.0185844
pmid:28985229
pmcid:PMC5630188
fatcat:64c577egijaohhndrd3kcjawfy