Medical Image Segmentation

187 papers with code • 28 benchmarks • 26 datasets

Medical image segmentation is the task of segmenting objects of interest in a medical image.

( Image credit: IVD-Net )

Latest papers with code

A Deep Learning-based Quality Assessment and Segmentation System with a Large-scale Benchmark Dataset for Optical Coherence Tomographic Angiography Image

shanzha09/COIPS 22 Jul 2021

The large-scale OCTA dataset is available at https://doi. org/10. 5281/zenodo. 5111975, https://doi. org/10. 5281/zenodo. 5111972.

Image Quality Assessment Medical Image Segmentation

22 Jul 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

Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation

neuro-ml/domain_shift_anatomy 10 Jul 2021

Domain Adaptation (DA) methods are widely used in medical image segmentation tasks to tackle the problem of differently distributed train (source) and test (target) data.

Domain Generalization Medical Image Segmentation +1

10 Jul 2021

UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation

plemeri/UACANet 6 Jul 2021

We construct a modified version of U-Net shape network with additional encoder and decoder and compute a saliency map in each bottom-up stream prediction module and propagate to the next prediction module.

Medical Image Segmentation

06 Jul 2021

Differentially private federated deep learning for multi-site medical image segmentation

TUM-AIMED/PrivateSegmentation 6 Jul 2021

The application of PTs to FL in medical imaging and the trade-offs between privacy guarantees and model utility, the ramifications on training performance and the susceptibility of the final models to attacks have not yet been conclusively investigated.

Federated Learning Medical Image Segmentation +1

06 Jul 2021

Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentation 2 Jul 2021

In this paper, we present a cooperative framework for training image segmentation models and a latent space augmentation method for generating hard examples.

Data Augmentation Image Reconstruction +2

02 Jul 2021

DivergentNets: Medical Image Segmentation by Network Ensemble

vlbthambawita/divergent-nets 1 Jul 2021

For our contribution to the EndoCV 2021 segmentation challenge, we propose two separate approaches.

Medical Image Segmentation Object Detection +1

01 Jul 2021

SinGAN-Seg: Synthetic Training Data Generation for Medical Image Segmentation

vlbthambawita/singan-seg-polyp 29 Jun 2021

We show that these synthetic data generation pipelines can be used as an alternative to bypass privacy concerns and as an alternative way to produce artificial segmentation datasets with corresponding ground truth masks to avoid the tedious medical data annotation process.

Medical Image Segmentation Semantic Segmentation +1

29 Jun 2021

Quality-Aware Memory Network for Interactive Volumetric Image Segmentation

0liliulei/Mem3D 20 Jun 2021

The proposed network has two appealing characteristics: 1) The memory-augmented network offers the ability to quickly encode past segmentation information, which will be retrieved for the segmentation of other slices; 2) The quality assessment module enables the model to directly estimate the qualities of segmentation predictions, which allows an active learning paradigm where users preferentially label the lowest-quality slice for multi-round refinement.

Active Learning Interactive Segmentation +2

20 Jun 2021