BESNet: boundary-enhanced segmentation of cells in histopathological images
… detects and segments cells from histopathological images. For training, a set of images and
… Detection and segmentation of cells are performed on the images for testing. The output is a …
… Detection and segmentation of cells are performed on the images for testing. The output is a …
Improved automatic detection and segmentation of cell nuclei in histopathology images
Y Al-Kofahi, W Lassoued, W Lee… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
… Building upon this study, and keeping in mind the challenges specific to histopathology
images noted earlier, we propose a method combining the LoG filter with automatic and adaptive …
images noted earlier, we propose a method combining the LoG filter with automatic and adaptive …
Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships
N Hatipoglu, G Bilgin - Medical & biological engineering & computing, 2017 - Springer
… are critical for cancer grade assessments, cellular and … histopathological images. In
response, we sought to identify a useful cell segmentation approach with histopathological images …
response, we sought to identify a useful cell segmentation approach with histopathological images …
Automatic cell nuclei segmentation and classification of breast cancer histopathology images
P Wang, X Hu, Y Li, Q Liu, X Zhu - Signal Processing, 2016 - Elsevier
… histopathological images remains the "gold standard" for breast cancer. The complexity of
breast cell histopathology (BCH) images … The histopathological images were acquired through …
breast cell histopathology (BCH) images … The histopathological images were acquired through …
Partitioning histopathological images: an integrated framework for supervised color-texture segmentation and cell splitting
… nature of histology images. The … cell segmentation and touching-cell splitting method that
can be used to deal with the outlined issues in computer-assisted histopathological image …
can be used to deal with the outlined issues in computer-assisted histopathological image …
[HTML][HTML] Deep learning of histopathology images at the single cell level
… analysis software already incorporates machine learning algorithms to assist researchers
and clinicians in quantifying and segmenting histopathological images. These tools have …
and clinicians in quantifying and segmenting histopathological images. These tools have …
Automatic cell segmentation in histopathological images via two-staged superpixel-based algorithms
A Albayrak, G Bilgin - Medical & biological engineering & computing, 2019 - Springer
… an emerging topic of the histopathological image-processing studies in the … segmentation
method to obtain cellular structures in high-dimensional histopathological images of renal cell …
method to obtain cellular structures in high-dimensional histopathological images of renal cell …
Cell‐type based semantic segmentation of histopathological images using deep convolutional neural networks
… , we propose a semantic segmentation method that can visually identify cell-type based … in
histopathological images and to emphasize clearly the type difference between cells. Thus, a …
histopathological images and to emphasize clearly the type difference between cells. Thus, a …
Learning-based mitotic cell detection in histopathological images
C Sommer, L Fiaschi, FA Hamprecht… - Proceedings of the …, 2012 - ieeexplore.ieee.org
… Several automatic methods based on image analysis have been … cell segmentation as
a first step followed by statistical analysis. Cell segmentation is achieved by traditional image …
a first step followed by statistical analysis. Cell segmentation is achieved by traditional image …
Unsupervised morphological segmentation of tissue compartments in histopathological images
… The automatic segmentation of cells and tissues in digitized histopathological images is an
essential … Ideally, a first step is to partition the image into distinct regions; followed by machine …
essential … Ideally, a first step is to partition the image into distinct regions; followed by machine …
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