The invention provides an MRI (
Magnetic Resonance Imaging)
brain tumor localization and intratumoral segmentation method based on a deep cascaded
convolution network, which comprises the steps of building a deep cascaded
convolution network segmentation model; performing model training and parameter optimization; and carrying out fast localization and intratumoral segmentation on a multi-
modal MRIbrain tumor. According to the
MRI brain tumor localization and intratumoral segmentation method provided by the invention based on the deep cascaded
convolution network, a deep cascaded
hybrid neuralnetwork formed by a full convolution neural network and a classified convolution neural network is constructed, the segmentation process is divided into a complete
tumor region localization phase andan intratumoral sub-region localization phase, and hierarchical
MRI brain tumor fast and accurate localization and intratumoral sub-region segmentation are realized. Firstly, the complete
tumor region is localized from an
MRI image by adopting a full convolution
network method, and then the complete tumor is further divided into an
edema region, a non-enhanced
tumor region, an enhanced tumor region and a
necrosis region by adopting an image classification method, and accurate localization for the multi-
modal MRI brain tumor and fast and
accurate segmentation for the intratumoral sub-regions are realized.