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Brain tumor segmentation is the task of segmenting tumors from other brain artefacts in MRI image of the brain.

( Image credit: Brain Tumor Segmentation with Deep Neural Networks )

Benchmarks

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Datasets

Greatest papers with code

nnU-Net for Brain Tumor Segmentation

2 Nov 2020MIC-DKFZ/nnunet

We apply nnU-Net to the segmentation task of the BraTS 2020 challenge.

BRAIN TUMOR SEGMENTATION DATA AUGMENTATION TUMOR SEGMENTATION

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

18 Mar 2016Kamnitsask/deepmedic

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation.

3D MEDICAL IMAGING SEGMENTATION BRAIN LESION SEGMENTATION FROM MRI BRAIN TUMOR SEGMENTATION LESION SEGMENTATION

3D MRI brain tumor segmentation using autoencoder regularization

27 Oct 2018black0017/MedicalZooPytorch

Automated segmentation of brain tumors from 3D magnetic resonance images (MRIs) is necessary for the diagnosis, monitoring, and treatment planning of the disease.

BRAIN TUMOR SEGMENTATION TUMOR SEGMENTATION

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

19 Aug 2019MrGiovanni/ModelsGenesis

More importantly, learning a model from scratch simply in 3D may not necessarily yield performance better than transfer learning from ImageNet in 2D, but our Models Genesis consistently top any 2D approaches including fine-tuning the models pre-trained from ImageNet as well as fine-tuning the 2D versions of our Models Genesis, confirming the importance of 3D anatomical information and significance of our Models Genesis for 3D medical imaging.

BRAIN TUMOR SEGMENTATION LIVER SEGMENTATION LUNG NODULE DETECTION LUNG NODULE SEGMENTATION PULMONARY EMBOLISM DETECTION SELF-SUPERVISED LEARNING TRANSFER LEARNING

Multi-scale self-guided attention for medical image segmentation

arXiv preprint 2019 sinAshish/Multi-Scale-Attention

In this paper we attempt to overcome these limitations with the proposed architecture, by capturing richer contextual dependencies based on the use of guided self-attention mechanisms.

ATTENTIVE SEGMENTATION NETWORKS BRAIN TUMOR SEGMENTATION DEEP ATTENTION

Brain Tumor Segmentation with Deep Neural Networks

13 May 2015naldeborgh7575/brain_segmentation

Finally, we explore a cascade architecture in which the output of a basic CNN is treated as an additional source of information for a subsequent CNN.

BRAIN TUMOR SEGMENTATION TUMOR SEGMENTATION

Autofocus Layer for Semantic Segmentation

22 May 2018yaq007/Autofocus-Layer

We propose the autofocus convolutional layer for semantic segmentation with the objective of enhancing the capabilities of neural networks for multi-scale processing.

BRAIN TUMOR SEGMENTATION TUMOR SEGMENTATION

KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation

4 Oct 2020jeya-maria-jose/KiU-Net-pytorch

To overcome this issue, we propose using an overcomplete convolutional architecture where we project our input image into a higher dimension such that we constrain the receptive field from increasing in the deep layers of the network.

3D MEDICAL IMAGING SEGMENTATION BRAIN TUMOR SEGMENTATION COMPUTED TOMOGRAPHY (CT) LIVER SEGMENTATION SEMANTIC SEGMENTATION ULTRASOUND VOLUMETRIC MEDICAL IMAGE SEGMENTATION