Tumor Segmentation

97 papers with code • 1 benchmarks • 5 datasets

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Latest papers with code

Optimized U-Net for Brain Tumor Segmentation

NVIDIA/DeepLearningExamples 7 Oct 2021

We propose an optimized U-Net architecture for a brain \mbox{tumor} segmentation task in the BraTS21 Challenge.

Brain Tumor Segmentation Tumor Segmentation

07 Oct 2021

E1D3 U-Net for Brain Tumor Segmentation: Submission to the RSNA-ASNR-MICCAI BraTS 2021 Challenge

clinical-and-translational-imaging-lab/brats-e1d3 6 Oct 2021

Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in medical image segmentation tasks.

Brain Tumor Segmentation Tumor Segmentation

06 Oct 2021

Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation

YaoZhang93/MAML 21 Jul 2021

To this end, we propose a novel mutual learning (ML) strategy for effective and robust multi-modal liver tumor segmentation.

Computed Tomography (CT) Medical Image Segmentation +1

21 Jul 2021

TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation

YaoZhang93/TumorCP 21 Jul 2021

Experiments on kidney tumor segmentation task demonstrate that TumorCP surpasses the strong baseline by a remarkable margin of 7. 12% on tumor Dice.

Data Augmentation Tumor Segmentation

21 Jul 2021

AGD-Autoencoder: Attention Gated Deep Convolutional Autoencoder for Brain Tumor Segmentation

timothy102/Brain-FMRI 7 Jul 2021

In this paper, we propose a novel attention gate (AG model) for brain tumor segmentation that utilizes both the edge detecting unit and the attention gated network to highlight and segment the salient regions from fMRI images.

Brain Segmentation Brain Tumor Segmentation +1

07 Jul 2021

Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation

hamghalam/MGP-VAE 7 Jul 2021

In large studies involving multi protocol Magnetic Resonance Imaging (MRI), it can occur to miss one or more sub-modalities for a given patient owing to poor quality (e. g. imaging artifacts), failed acquisitions, or hallway interrupted imaging examinations.

Brain Tumor Segmentation Tumor Segmentation

07 Jul 2021

ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities

Wangyixinxin/ACN 28 Jun 2021

Specifically, ACN adopts a novel co-training network, which enables a coupled learning process for both full modality and missing modality to supplement each other's domain and feature representations, and more importantly, to recover the `missing' information of absent modalities.

Brain Tumor Segmentation Transfer Learning +1

28 Jun 2021

Brain tumour segmentation using a triplanar ensemble of U-Nets

vaanathi/truenet_tumseg 24 May 2021

Our method achieved an evaluation score that was the equal 5th highest value (with our method ranking in 10th place) in the BraTS'20 challenge, with mean Dice values of 0. 81, 0. 89 and 0. 84 on ET, WT and TC regions respectively on the BraTS'20 unseen test dataset.

Brain Tumor Segmentation Tumor Segmentation

24 May 2021

Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain Adaptation

KeleiHe/BiGL 17 May 2021

Specifically, a bidirectional image synthesis and segmentation module is proposed to segment the brain tumor using the intermediate data distributions generated for the two domains, which includes an image-to-image translator and a shared-weighted segmentation network.

Brain Tumor Segmentation Image Generation +2

17 May 2021