3D Medical Imaging Segmentation
32 papers with code • 1 benchmarks • 9 datasets
3D medical imaging segmentation is the task of segmenting medical objects of interest from 3D medical imaging.
( Image credit: Elastic Boundary Projection for 3D Medical Image Segmentation )
Benchmarks
These leaderboards are used to track progress in 3D Medical Imaging Segmentation
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Libraries
Use these libraries to find 3D Medical Imaging Segmentation models and implementationsDatasets
VerSe
SKM-TEA
KiTS19
ATLAS v2.0
HaN-Seg
BHSD
Most implemented papers
A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
Here we present a method for the simultaneous segmentation of white matter lesions and normal-appearing neuroanatomical structures from multi-contrast brain MRI scans of multiple sclerosis patients.
A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis.
KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation
jeya-maria-jose/KiU-Net-pytorch
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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.
Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
DL+DiReCT is a promising combination of a deep learning‐based method with a traditional registration technique to detect subtle changes in cortical thickness.
Automated Segmentation and Connectivity Analysis for Normal Pressure Hydrocephalus
UCSB-VRL/NPH_Prediction
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BME Frontiers 2022
The segmentation and network features are used to train a model for NPH prediction.
An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation
The scarcity of pixel-level annotation is a prevalent problem in medical image segmentation tasks.
Dynamic Linear Transformer for 3D Biomedical Image Segmentation
Transformer-based neural networks have surpassed promising performance on many biomedical image segmentation tasks due to a better global information modeling from the self-attention mechanism.
An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation
In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans.
Reliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis
SCAN-NRAD/DL-DiReCT
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Human Brain Mapping 2022
The segmentations were derived with FreeSurfer from the non-enhanced image and used as ground truth for the coregistered CE image.
SegReg: Segmenting OARs by Registering MR Images and CT Annotations
This manual process is highly time-consuming and expensive, limiting the number of patients who can receive timely radiotherapy.
