A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
A review: The detection of cancer cells in histopathology based on machine vision
W He, T Liu, Y Han, W Ming, J Du, Y Liu, Y Yang… - Computers in Biology …, 2022 - Elsevier
Abstract Machine vision is being employed in defect detection, size measurement, pattern
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …
Deep adversarial training for multi-organ nuclei segmentation in histopathology images
Nuclei mymargin segmentation is a fundamental task for various computational pathology
applications including nuclei morphology analysis, cell type classification, and cancer …
applications including nuclei morphology analysis, cell type classification, and cancer …
[HTML][HTML] Role of tumor infiltrating lymphocytes and spatial immune heterogeneity in sensitivity to PD-1 axis blockers in non-small cell lung cancer
Background Tumor infiltrating lymphocytes (TILs) reflect adaptive antitumor immune
responses in cancer and are generally associated with favorable prognosis. However, the …
responses in cancer and are generally associated with favorable prognosis. However, the …
Reduction of cardiac fibrosis by interference with YAP-dependent transactivation
Background: Conversion of cardiac stromal cells into myofibroblasts is typically associated
with hypoxia conditions, metabolic insults, and/or inflammation, all of which are predisposing …
with hypoxia conditions, metabolic insults, and/or inflammation, all of which are predisposing …
Stain Color Adaptive Normalization (SCAN) algorithm: Separation and standardization of histological stains in digital pathology
Background and objective The diagnosis of histopathological images is based on the visual
analysis of tissue slices under a light microscope. However, the histological tissue …
analysis of tissue slices under a light microscope. However, the histological tissue …
A hybrid deep learning approach for gland segmentation in prostate histopathological images
Background In digital pathology, the morphology and architecture of prostate glands have
been routinely adopted by pathologists to evaluate the presence of cancer tissue. The …
been routinely adopted by pathologists to evaluate the presence of cancer tissue. The …
Robust nuclei segmentation in histopathology using ASPPU-Net and boundary refinement
Automated nuclear segmentation in histopathological images is a prerequisite for a
computer-aided diagnosis framework. However, it remains a challenging problem due to the …
computer-aided diagnosis framework. However, it remains a challenging problem due to the …
A pathomic approach for tumor-infiltrating lymphocytes classification on breast cancer digital pathology images
Background and objectives The detection of tumor-infiltrating lymphocytes (TILs) could aid in
the development of objective measures of the infiltration grade and can support decision …
the development of objective measures of the infiltration grade and can support decision …
Nuclei and glands instance segmentation in histology images: a narrative review
Examination of tissue biopsy and quantification of the various characteristics of cellular
processes are clinical benchmarks in cancer diagnosis. Nuclei and glands instance …
processes are clinical benchmarks in cancer diagnosis. Nuclei and glands instance …