Brain Image Segmentation
17 papers with code • 6 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Brain Image Segmentation
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CREMI
Latest papers with no code
The Method of Multimodal MRI Brain Image Segmentation Based on Differential Geometric Features
In this paper, we use the differential geometric information including JD and CV as image characteristics to measure the differences between different MRI images, which represent local size changes and local rotations of the brain image, and we can use them as one CNN channel with other three modalities (T1-weighted, T1-IR and T2-FLAIR) to get more accurate results of brain segmentation.
Towards integrating spatial localization in convolutional neural networks for brain image segmentation
In this work, we propose different ways to introduce spatial constraints into the network to further reduce prediction inconsistencies.
Combination of Hidden Markov Random Field and Conjugate Gradient for Brain Image Segmentation
Hidden Markov Random Field model is one of several techniques used in image segmentation.
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation
In contrast, Multi-Dimensional Recurrent NNs (MD-RNNs) can perceive the entire spatio-temporal context of each pixel in a few sweeps through all pixels, especially when the RNN is a Long Short-Term Memory (LSTM).
