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Cascade Residual Multiscale Convolution and Mamba-Structured UNet for Advanced Brain Tumor Image Segmentation

Entropy (Basel, Switzerland), 2024-05, Vol.26 (5), p.385

2024

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White Matter, Gray Matter and Cerebrospinal Fluid Segmentation from Brain Magnetic Resonance Imaging Using Adaptive U-Net and Local Convolutional Neural Network

Computer journal, 2022-12, Vol.65 (12), p.3081-3090

2022

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Brain Magnetic Resonance Imaging Segmentation Using Possibilistic Clustering Algorithm Combined with Context Constraints

Journal of medical imaging and health informatics, 2020-07, Vol.10 (7), p.1669-1674

2020

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UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

IEEE transactions on medical imaging, 2020-06, Vol.39 (6), p.1856-1867

2020

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Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning

IEEE transactions on medical imaging, 2018-07, Vol.37 (7), p.1562-1573

2018

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DRINet for Medical Image Segmentation

IEEE transactions on medical imaging, 2018-11, Vol.37 (11), p.2453-2462

2018

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VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images

NeuroImage (Orlando, Fla.), 2018-04, Vol.170, p.446-455

2018

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Optimization and comparative evaluation of nonlinear deformation algorithms for atlas-based segmentation of DBS target nuclei

NeuroImage (Orlando, Fla.), 2019-01, Vol.184, p.586-598

2019

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Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI

Journal of magnetic resonance imaging, 2020-01, Vol.51 (1), p.175-182

2020

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Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

IEEE transactions on medical imaging, 2017-11, Vol.36 (11), p.2319-2330

2017

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DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

IEEE transactions on pattern analysis and machine intelligence, 2019-07, Vol.41 (7), p.1559-1572

2019

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3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

NeuroImage (Orlando, Fla.), 2018-04, Vol.170, p.456-470

2018

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Concatenated and Connected Random Forests With Multiscale Patch Driven Active Contour Model for Automated Brain Tumor Segmentation of MR Images

IEEE transactions on medical imaging, 2018-08, Vol.37 (8), p.1943-1954

2018

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Brain tumor segmentation and classification from magnetic resonance images: Review of selected methods from 2014 to 2019

Pattern recognition letters, 2020-03, Vol.131, p.244-260

2020

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Segmentation of stroke lesions using transformers‐augmented MRI analysis

Human brain mapping, 2024-08, Vol.45 (11), p.e26803-n/a

2024

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Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan

NeuroImage (Orlando, Fla.), 2020-03, Vol.208, p.116450-116450, Article 116450

2020

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3D AGSE-VNet: an automatic brain tumor MRI data segmentation framework

BMC medical imaging, 2022-01, Vol.22 (1), p.6-6, Article 6

2022

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Automatic Segmentation of Acute Ischemic Stroke From DWI Using 3-D Fully Convolutional DenseNets

IEEE transactions on medical imaging, 2018-09, Vol.37 (9), p.2149-2160

2018

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Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools

Computers in biology and medicine, 2023-01, Vol.152, p.106405-106405, Article 106405

2023

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FastSurfer - A fast and accurate deep learning based neuroimaging pipeline

NeuroImage (Orlando, Fla.), 2020-10, Vol.219, p.117012-117012, Article 117012

2020

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Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities

IEEE transactions on image processing, 2021-01, Vol.30, p.4263-4274

2021

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SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

IEEE transactions on medical imaging, 2019-04, Vol.38 (4), p.1016-1025

2019

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Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Journal of medical systems, 2019-09, Vol.43 (9), p.294-10, Article 294

2019

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Multi-Domain Image Completion for Random Missing Input Data

IEEE transactions on medical imaging, 2021-04, Vol.40 (4), p.1113-1122

2021

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Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

IEEE reviews in biomedical engineering, 2023, Vol.16, p.70-90

2023

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Cascade Residual Multiscale Convolution and Mamba-Structured UNet for Advanced Brain Tumor Image Segmentation

White Matter, Gray Matter and Cerebrospinal Fluid Segmentation from Brain Magnetic Resonance Imaging Using Adaptive U-Net and Local Convolutional Neural Network

Brain Magnetic Resonance Imaging Segmentation Using Possibilistic Clustering Algorithm Combined with Context Constraints

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning

DRINet for Medical Image Segmentation

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images

Optimization and comparative evaluation of nonlinear deformation algorithms for atlas-based segmentation of DBS target nuclei

Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI

Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

Concatenated and Connected Random Forests With Multiscale Patch Driven Active Contour Model for Automated Brain Tumor Segmentation of MR Images

Brain tumor segmentation and classification from magnetic resonance images: Review of selected methods from 2014 to 2019

Segmentation of stroke lesions using transformers‐augmented MRI analysis

Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan

3D AGSE-VNet: an automatic brain tumor MRI data segmentation framework

Automatic Segmentation of Acute Ischemic Stroke From DWI Using 3-D Fully Convolutional DenseNets

Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools

FastSurfer - A fast and accurate deep learning based neuroimaging pipeline

Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities

SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Multi-Domain Image Completion for Random Missing Input Data

Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

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