<p>Images of bacterial and mammalian cells were segmented using trained conv-nets and additional downstream processing. Thresholding for bacterial cells and an active contour based approach for mammalian cells were used to convert the conv-net prediction into a segmentation mask.</p
The characteristics of tissue cells in different shapes,sizes and varied textures make it difficult ...
The immunofluorescence confocal microscopy images of three different cell lines: MCF-10A, MCF-7 and ...
The obtained contour is indicated by the black line that is overlaid on each image. All images were ...
The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck fo...
This work examines the use of convolutional neural networks with a focus on semantic and instance se...
Image object segmentation allows localising the region of interest in the image (ROI) and separating...
In this thesis a semi-automated cell analysis system is described through image processing. To achie...
This work introduces methods for single-cell segmentation of microscopy images. The developed method...
Motivation: Single-cell time-lapse microscopy is a ubiquitous tool for studying the dynamics of comp...
The quantification and identification of cellular phenotypes from high-content microscopy images has...
This paper proposes a novel approach for image segmentation in the context of biomedical application...
With the rapid increases in hardware capability in recent years, machine learning is becoming more p...
Mechanical cues such as stresses and strains are now recognized as essential regulators in many biol...
Cell culture monitoring necessitates thorough attention for the continuous characterization of culti...
International audienceImage segmentation is a field that has known huge breakthroughs this last deca...
The characteristics of tissue cells in different shapes,sizes and varied textures make it difficult ...
The immunofluorescence confocal microscopy images of three different cell lines: MCF-10A, MCF-7 and ...
The obtained contour is indicated by the black line that is overlaid on each image. All images were ...
The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck fo...
This work examines the use of convolutional neural networks with a focus on semantic and instance se...
Image object segmentation allows localising the region of interest in the image (ROI) and separating...
In this thesis a semi-automated cell analysis system is described through image processing. To achie...
This work introduces methods for single-cell segmentation of microscopy images. The developed method...
Motivation: Single-cell time-lapse microscopy is a ubiquitous tool for studying the dynamics of comp...
The quantification and identification of cellular phenotypes from high-content microscopy images has...
This paper proposes a novel approach for image segmentation in the context of biomedical application...
With the rapid increases in hardware capability in recent years, machine learning is becoming more p...
Mechanical cues such as stresses and strains are now recognized as essential regulators in many biol...
Cell culture monitoring necessitates thorough attention for the continuous characterization of culti...
International audienceImage segmentation is a field that has known huge breakthroughs this last deca...
The characteristics of tissue cells in different shapes,sizes and varied textures make it difficult ...
The immunofluorescence confocal microscopy images of three different cell lines: MCF-10A, MCF-7 and ...
The obtained contour is indicated by the black line that is overlaid on each image. All images were ...