Original images are from http://www.robots.ox.ac.uk/~vgg/software/cell_detection/. This software is associated with the publication "Learning to Detect Cells Using Non-overlapping Extremal Regions", MICCAI 2012. (DOI: 10.1007/978-3-642-33415-3_43) Here, we provide the ground truth labels of: cell centers and segmentation, which are used in the publications: "Learning to Segment: Training Hierarchical Segmentation under a Topological Loss", MICCAI 2015. (DOI: 10.1007/978-3-319-24574-4_32) "Cell Detection and Segmentation Using Correlation Clustering", MICCAI 2014. (DOI: 10.1007/978-3-319-10404-1_2
Light microscopy combined with well-established protocols of two-dimensional cell culture facilitate...
the potential to provide treatments for cancer, Parkinson’s disease, Huntington’s disease, Type 1 di...
These images are for testing with the self-supervised machine learning demo code posted to GitHub. ...
Original images are from http://www-bcf.usc.edu/~forsburg/pombeX.html. This software is associated w...
Dataset used to evaluate the method described in "Yeast cell detection and segmentation in bright fi...
In this paper, we propose a fully automated learning based approach for detecting cells in time-laps...
This is a data set that contains labelled HeLa cell images, indicating the four different classes - ...
This is a data set that contains 300 labelled HeLa cell images, indicating the five different classe...
The process of cellular detection and tracking is a key task in the analysis of cellular motility an...
Cell detection and classification in histology images is one of the most important tasks in computat...
Name: Phase contrast images of bacteria Data type: Paired microscopy images and corresponding labe...
This paper proposes a bio-driven algorithm that detects cell regions automatically in the human embr...
<p>(A) For the negative phase contrast image, peaks of light intensity are detected for all cells, a...
Abstract — This paper proposes an automated detection method with simple algorithm for detecting hum...
<p>(A) Raw negative phase contrast images. (B) Segmentation result with false segmented cells pointe...
Light microscopy combined with well-established protocols of two-dimensional cell culture facilitate...
the potential to provide treatments for cancer, Parkinson’s disease, Huntington’s disease, Type 1 di...
These images are for testing with the self-supervised machine learning demo code posted to GitHub. ...
Original images are from http://www-bcf.usc.edu/~forsburg/pombeX.html. This software is associated w...
Dataset used to evaluate the method described in "Yeast cell detection and segmentation in bright fi...
In this paper, we propose a fully automated learning based approach for detecting cells in time-laps...
This is a data set that contains labelled HeLa cell images, indicating the four different classes - ...
This is a data set that contains 300 labelled HeLa cell images, indicating the five different classe...
The process of cellular detection and tracking is a key task in the analysis of cellular motility an...
Cell detection and classification in histology images is one of the most important tasks in computat...
Name: Phase contrast images of bacteria Data type: Paired microscopy images and corresponding labe...
This paper proposes a bio-driven algorithm that detects cell regions automatically in the human embr...
<p>(A) For the negative phase contrast image, peaks of light intensity are detected for all cells, a...
Abstract — This paper proposes an automated detection method with simple algorithm for detecting hum...
<p>(A) Raw negative phase contrast images. (B) Segmentation result with false segmented cells pointe...
Light microscopy combined with well-established protocols of two-dimensional cell culture facilitate...
the potential to provide treatments for cancer, Parkinson’s disease, Huntington’s disease, Type 1 di...
These images are for testing with the self-supervised machine learning demo code posted to GitHub. ...