Medical Image Segmentation

173 papers with code • 30 benchmarks • 28 datasets

Medical image classification is the task of classifying objects of interest in a medical image.

( Image credit: IVD-Net )

Greatest papers with code

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

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

qubvel/segmentation_models.pytorch 18 Jul 2018

Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet

Medical Image Segmentation Semantic Segmentation

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

Segmentation Loss Odyssey

JunMa11/SegLoss 27 May 2020

Loss functions are one of the crucial ingredients in deep learning-based medical image segmentation methods.

Medical Image Segmentation Semantic Segmentation

Automated Design of Deep Learning Methods for Biomedical Image Segmentation

MIC-DKFZ/nnunet 17 Apr 2019

Biomedical imaging is a driver of scientific discovery and core component of medical care, currently stimulated by the field of deep learning.

Medical Image Segmentation Semantic Segmentation

UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

PaddlePaddle/PaddleSeg 19 Apr 2020

UNet, which is one of deep learning networks with an encoder-decoder architecture, is widely used in medical image segmentation.

Medical Image Segmentation Semantic Segmentation

Attention U-Net: Learning Where to Look for the Pancreas

PaddlePaddle/PaddleSeg 11 Apr 2018

We propose a novel attention gate (AG) model for medical imaging that automatically learns to focus on target structures of varying shapes and sizes.

Pancreas Segmentation Semantic Segmentation

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

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

MrGiovanni/Nested-UNet 11 Dec 2019

The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN).

 Ranked #1 on Medical Image Segmentation on EM (IoU metric)

Computed Tomography (CT) Electron Microscopy +3

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