Volumetric Medical Image Segmentation

17 papers with code • 1 benchmarks • 2 datasets

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Use these libraries to find Volumetric Medical Image Segmentation models and implementations

Most implemented papers

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

faustomilletari/VNet 15 Jun 2016

Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields.

On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

gift-surg/HighRes3DNet 6 Jul 2017

To illustrate its efficiency of learning 3D representation from large-scale image data, the proposed network is validated with the challenging task of parcellating 155 neuroanatomical structures from brain MR images.

Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation

MiguelMonteiro/CRFasRNNLayer 19 Jul 2018

In this paper, we test whether this algorithm, which was shown to improve semantic segmentation for 2D RGB images, is able to improve segmentation quality for 3D multi-modal medical images.

nnFormer: Interleaved Transformer for Volumetric Segmentation

282857341/nnformer 7 Sep 2021

Transformer, the model of choice for natural language processing, has drawn scant attention from the medical imaging community.

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.

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

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

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.

Positional Contrastive Learning for Volumetric Medical Image Segmentation

dewenzeng/positional_cl 16 Jun 2021

The success of deep learning heavily depends on the availability of large labeled training sets.

A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

himashi92/vt-unet 26 Nov 2021

We propose a Transformer architecture for volumetric segmentation, a challenging task that requires keeping a complex balance in encoding local and global spatial cues, and preserving information along all axes of the volume.

Memory-efficient Segmentation of High-resolution Volumetric MicroCT Images

virgil3706/memory-efficient-u-net 31 May 2022

In this work, we propose a novel memory-efficient network architecture for 3D high-resolution image segmentation.

Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation

jianf-wang/gbdl CVPR 2022

Secondly, in fact, they are only partially based on Bayesian deep learning, as their overall architectures are not designed under the Bayesian framework.