MRI segmentation

43 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

A Learning Strategy for Contrast-agnostic MRI Segmentation

BBillot/SynthSeg MIDL 2019

These samples are produced using the generative model of the classical Bayesian segmentation framework, with randomly sampled parameters for appearance, deformation, noise, and bias field.

Acute and sub-acute stroke lesion segmentation from multimodal MRI

NIC-VICOROB/SUNet-architecture 31 Oct 2018

Acute stroke lesion segmentation tasks are of great clinical interest as they can help doctors make better informed treatment decisions.

Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

adalca/neuron CVPR 2018

The integration of anatomical priors can facilitate CNN-based anatomical segmentation in a range of novel clinical problems, where few or no annotations are available and thus standard networks are not trainable.

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

ad12/DOSMA 29 Apr 2020

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression.

Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

LucasFidon/label-set-loss-functions 8 Jul 2021

Deep neural networks have increased the accuracy of automatic segmentation, however, their accuracy depends on the availability of a large number of fully segmented images.

3D Densely Convolutional Networks for Volumetric Segmentation

tbuikr/3D_DenseSeg 11 Sep 2017

The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.

3D Densely Convolutional Networks for VolumetricSegmentation

black0017/MedicalZooPytorch arXiv preprint 2017

The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.

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

josedolz/LiviaNET 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.

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

josedolz/SemiDenseNet 14 Dec 2017

We report evaluations of our method on the public data of the MICCAI iSEG-2017 Challenge on 6-month infant brain MRI segmentation, and show very competitive results among 21 teams, ranking first or second in most metrics.

Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

voxelmorph/voxelmorph 25 Apr 2019

To develop a deep learning-based segmentation model for a new image dataset (e. g., of different contrast), one usually needs to create a new labeled training dataset, which can be prohibitively expensive, or rely on suboptimal ad hoc adaptation or augmentation approaches.