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 without code

Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation

no code yet • 21 Jul 2021

Learning segmentation from noisy labels is an important task for medical image analysis due to the difficulty in acquiring highquality annotations.

Medical Image Segmentation Semantic Segmentation

Transductive image segmentation: Self-training and effect of uncertainty estimation

no code yet • 19 Jul 2021

It focuses on the quality of predictions made on the unlabeled data of interest when they are included for optimization during training, rather than improving generalization.

Medical Image Segmentation Semantic Segmentation

LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation

no code yet • 19 Jul 2021

Medical image segmentation plays an essential role in developing computer-assisted diagnosis and therapy systems, yet still faces many challenges.

Medical Image Segmentation Semantic Segmentation

TransClaw U-Net: Claw U-Net with Transformers for Medical Image Segmentation

no code yet • 12 Jul 2021

The convolution part is applied for extracting the shallow spatial features to facilitate the recovery of the image resolution after upsampling.

Medical Image Segmentation Semantic Segmentation

The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization in Medical Image Segmentation

no code yet • 12 Jul 2021

First, we show higher correlation to using full data for training when testing on the external validation set using smaller proxy data than a random selection of the proxy data.

AutoML Medical Image Segmentation +1

TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation

no code yet • 12 Jul 2021

With the development of deep encoder-decoder architectures and large-scale annotated medical datasets, great progress has been achieved in the development of automatic medical image segmentation.

Medical Image Segmentation Semantic Segmentation

A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation

no code yet • 11 Jul 2021

Hence, we propose a new spatial guided self-supervised clustering network (SGSCN) for medical image segmentation, where we introduce multiple loss functions designed to aid in grouping image pixels that are spatially connected and have similar feature representations.

Medical Image Segmentation Semantic Segmentation

Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation

no code yet • 10 Jul 2021

Unlike the current literature on task-specific self-supervised pretraining followed by supervised fine-tuning, we utilize SSL to learn task-agnostic knowledge from heterogeneous data for various medical image segmentation tasks.

Medical Image Segmentation Representation Learning +2

Towards Robust General Medical Image Segmentation

no code yet • 9 Jul 2021

The reliability of Deep Learning systems depends on their accuracy but also on their robustness against adversarial perturbations to the input data.

Image Classification Medical Image Segmentation +1

Label noise in segmentation networks : mitigation must deal with bias

no code yet • 5 Jul 2021

In this work, we explore biased and unbiased errors artificially introduced to brain tumour annotations on MRI data.

Medical Image Segmentation Semantic Segmentation