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Infant Brain Mri Segmentation

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InfiNet: Fully Convolutional Networks for Infant Brain MRI Segmentation

11 Oct 2018

We present a novel, parameter-efficient and practical fully convolutional neural network architecture, termed InfiNet, aimed at voxel-wise semantic segmentation of infant brain MRI images at iso-intense stage, which can be easily extended for other segmentation tasks involving multi-modalities.

INFANT BRAIN MRI SEGMENTATION SEMANTIC SEGMENTATION

Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets: Application to IsoIntense Infant Brain MRI Segmentation

21 Sep 2018

Using our proposed training strategy based on similarity loss functions and patch prediction fusion we decrease the number of parameters in the network, reduce the complexity of the training process focusing the attention on less number of tasks, while mitigating the effects of data imbalance between labels and inaccuracies near patch borders.

INFANT BRAIN MRI SEGMENTATION SEMANTIC SEGMENTATION

Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation

28 Nov 2017

We present a method to address the challenging problem of segmentation of multi-modality isointense infant brain MR images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF).

INFANT BRAIN MRI SEGMENTATION SEMANTIC SEGMENTATION

Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network

16 Oct 2017

Neonatal brain segmentation in magnetic resonance (MR) is a challenging problem due to poor image quality and low contrast between white and gray matter regions.

BRAIN SEGMENTATION INFANT BRAIN MRI SEGMENTATION

Isointense infant brain MRI segmentation with a dilated convolutional neural network

9 Aug 2017

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter.

INFANT BRAIN MRI SEGMENTATION