Cell Segmentation

26 papers with code • 2 benchmarks • 0 datasets

Cell Segmentation is a task of splitting a microscopic image domain into segments, which represent individual instances of cells. It is a fundamental step in many biomedical studies, and it is regarded as a cornerstone of image-based cellular research. Cellular morphology is an indicator of a physiological state of the cell, and a well-segmented image can capture biologically relevant morphological information.

Source: Cell Segmentation by Combining Marker-controlled Watershed and Deep Learning


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

PolarMask++: Enhanced Polar Representation for Single-Shot Instance Segmentation and Beyond

xieenze/PolarMask 5 May 2021

Extensive experiments demonstrate the effectiveness of both PolarMask and PolarMask++, which achieve competitive results on instance segmentation in the challenging COCO dataset with single-model and single-scale training and testing, as well as new state-of-the-art results on rotate text detection and cell segmentation.

Ranked #31 on Instance Segmentation on COCO test-dev (using extra training data)

Cell Segmentation Instance Segmentation +2

Cell Detection with Star-convex Polygons

mpicbg-csbd/stardist 9 Jun 2018

Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications.

Cell Segmentation

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

HzFu/MNet_DeepCDR 7 Mar 2019

In this paper, we propose a context encoder network (referred to as CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation.

 Ranked #1 on Lung Nodule Segmentation on LUNA (Accuracy metric)

Cell Segmentation Optic Disc Segmentation +1

DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

DebeshJha/2020-CBMS-DoubleU-Net 8 Jun 2020

The encouraging results, produced on various medical image segmentation datasets, show that DoubleU-Net can be used as a strong baseline for both medical image segmentation and cross-dataset evaluation testing to measure the generalizability of Deep Learning (DL) models.

Cell Segmentation Colorectal Polyps Characterization +4

Microscopy Cell Segmentation via Convolutional LSTM Networks

arbellea/LSTM-UNet 29 May 2018

Live cell microscopy sequences exhibit complex spatial structures and complicated temporal behaviour, making their analysis a challenging task.

Cell Segmentation

Attention-Based Transformers for Instance Segmentation of Cells in Microstructures

ChristophReich1996/Cell-DETR 19 Nov 2020

For the specific use case, the proposed method surpasses the state-of-the-art tools for semantic segmentation and additionally predicts the individual object instances.

Cell Segmentation Instance Segmentation +1

Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response

naivete5656/WSISPDR 29 Nov 2019

In addition, we demonstrated that our method can perform without any annotation by using fluorescence images that cell nuclear were stained as training data.

Cell Segmentation Instance Segmentation +1

Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features

SAIL-GuoLab/Cell_Segmentation_and_Tracking 15 Jan 2020

The ability to extrapolate gene expression dynamics in living single cells requires robust cell segmentation, and one of the challenges is the amorphous or irregularly shaped cell boundaries.

Cell Segmentation