Lesion Segmentation

87 papers with code • 6 benchmarks • 7 datasets

Lesion segmentation is the task of segmenting out lesions from other objects in medical based images.

( Image credit: D-UNet )

Greatest papers with code

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

tensorflow/models ECCV 2018

The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter networks can capture sharper object boundaries by gradually recovering the spatial information.

Ranked #2 on Semantic Segmentation on PASCAL VOC 2012 test (using extra training data)

Image Classification Lesion Segmentation +1

U-Net: Convolutional Networks for Biomedical Image Segmentation

milesial/Pytorch-UNet 18 May 2015

There is large consent that successful training of deep networks requires many thousand annotated training samples.

Cell Segmentation Colorectal Gland Segmentation: +8

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

osmr/imgclsmob 2 Nov 2015

We show that SegNet provides good performance with competitive inference time and more efficient inference memory-wise as compared to other architectures.

Crowd Counting General Classification +4

Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

LeeJunHyun/Image_Segmentation 20 Feb 2018

In this paper, we propose a Recurrent Convolutional Neural Network (RCNN) based on U-Net as well as a Recurrent Residual Convolutional Neural Network (RRCNN) based on U-Net models, which are named RU-Net and R2U-Net respectively.

Image Classification Lesion Segmentation +4

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Kamnitsask/deepmedic 26 May 2019

With all three datasets combined, the current system compared to previous methods also attained a reliably higher cross-validation accuracy.

Lesion Segmentation

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

Kamnitsask/deepmedic 18 Mar 2016

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation.

3D Medical Imaging Segmentation Brain Lesion Segmentation From Mri +2

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

xmengli999/H-DenseUNet 21 Sep 2017

Our method outperformed other state-of-the-arts on the segmentation results of tumors and achieved very competitive performance for liver segmentation even with a single model.

Automatic Liver And Tumor Segmentation Lesion Segmentation +2

Boundary loss for highly unbalanced segmentation

LIVIAETS/surface-loss 17 Dec 2018

We propose a boundary loss, which takes the form of a distance metric on the space of contours, not regions.

Brain Lesion Segmentation From Mri Ischemic Stroke Lesion Segmentation +3

Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation

rezazad68/BCDU-Net 10 Mar 2020

These blocks adaptively recalibrate the channel-wise feature responses by utilizing a self-gating mechanism of the global information embedding of the feature maps.

Lesion Segmentation Semantic Segmentation