… 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 …

… 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 …

… are critical for cancer grade assessments, cellular and … histopathological images. In
response, we sought to identify a useful cell segmentation approach with histopathological images …

… histopathological images remains the "gold standard" for breast cancer. The complexity of
breast cell histopathology (BCH) images … The histopathological images were acquired through …

… 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 …

… analysis software already incorporates machine learning algorithms to assist researchers
and clinicians in quantifying and segmenting histopathological images. These tools have …

… 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 …

… , 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 …

… 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 …

… 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 …