AIMC Topic: Hematoxylin

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A Computer-Aided Diagnosis System of Fetal Nucleated Red Blood Cells With Convolutional Neural Network.

Archives of pathology & laboratory medicine Nov 1, 2022
CONTEXT.—: The rapid recognition of fetal nucleated red blood cells (fNRBCs) presents considerable challenges.
Neural Networks, Computer Computers Humans Paraffin Eosine Yellowish-(YS) Hematoxylin Formaldehyde Erythrocytes
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BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.

Database : the journal of biological databases and curation Oct 17, 2022
Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women. Advances in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer ...
Hematoxylin Artificial Intelligence Humans Female Breast Neoplasms Algorithms Eosine Yellowish-(YS)
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Dual Encoder Attention U-net for Nuclei Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Nuclei segmentation in whole slide images (WSIs) stained with Hematoxylin and Eosin (H&E) dye, is a key step in computational pathology which aims to automate the laborious process of manual counting and segmentation. Nuclei segmentation is a challen...
Neural Networks, Computer Image Processing, Computer-Assisted Hematoxylin Cell Nucleus Eosine Yellowish-(YS)
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[Application of deep learning neural network in pathological image classification of non-inflammatory aortic membrane degeneration].

Zhonghua bing li xue za zhi = Chinese journal of pathology Jun 8, 2021
To investigate the value of deep learning in classifying non-inflammatory aortic membrane degeneration. Eighty-nine cases of non-inflammatory aortic media degeneration diagnosed from January to June 2018 were collected at Beijing Anzhen Hospital, C...
Neural Networks, Computer Artificial Intelligence Hematoxylin Deep Learning China
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AI Neuropathologist: an innovative technology enabling a faultless pathological diagnosis?

Neuro-oncology Jan 30, 2021
Neuropathology Eosine Yellowish-(YS) Hematoxylin Humans Artificial Intelligence Deep Learning Glioma Technology
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Artificial intelligence neuropathologist for glioma classification using deep learning on hematoxylin and eosin stained slide images and molecular markers.

Neuro-oncology Jan 30, 2021
BACKGROUND: Pathological diagnosis of glioma subtypes is essential for treatment planning and prognosis. Standard histological diagnosis of glioma is based on postoperative hematoxylin and eosin stained slides by neuropathologists. With advancing art...
Hematoxylin Neuropathology Artificial Intelligence Deep Learning Glioma Eosine Yellowish-(YS) Humans
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Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.

The Lancet. Oncology Jan 1, 2021
BACKGROUND: Detecting microsatellite instability (MSI) in colorectal cancer is crucial for clinical decision making, as it identifies patients with differential treatment response and prognosis. Universal MSI testing is recommended, but many patients...
Genetic Predisposition to Disease Staining and Labeling Microsatellite Instability Coloring Agents Predictive Value of Tests Eosine Yellowish-(YS) Humans Hematoxylin Diagnosis, Computer-Assisted Phenotype Microscopy Reproducibility of Results Deep Learning Image Interpretation, Computer-Assisted Colorectal Neoplasms
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Deep learning for prediction of colorectal cancer outcome: a discovery and validation study.

Lancet (London, England) Feb 1, 2020
BACKGROUND: Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal ...
Cohort Studies Early Detection of Cancer Hematoxylin Aged Prognosis Biomarkers, Tumor Middle Aged Kaplan-Meier Estimate Humans Female Colorectal Neoplasms Deep Learning Male Eosine Yellowish-(YS) Prospective Studies
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