Automatic nuclei segmentation in H&E stained breast cancer histopathology images. - Wikidata - awgldk - TriplyDB

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

http://www.wikidata.org/entity/Q34906509

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Therapeutic antibodies reveal Notch control of transdifferentiation in the adult lung New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images Transcription factor Etv5 is essential for the maintenance of alveolar type II cells.Dual leucine zipper kinase-dependent PERK activation contributes to neuronal degeneration following insult.Automated grading of renal cell carcinoma using whole slide imaging A computer-based automated algorithm for assessing acinar cell loss after experimental pancreatitis.Adaptive localization of focus point regions via random patch probabilistic density from whole-slide, Ki-67-stained brain tumor tissue Using Automated Image Analysis Algorithms to Distinguish Normal, Aberrant, and Degenerate Mitotic Figures Induced by Eg5 Inhibition.Automated Segmentation of Nuclei in Breast Cancer Histopathology Images.Enhancements in localized classification for uterine cervical cancer digital histology image assessment.A robust nonlinear tissue-component discrimination method for computational pathology.Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.Mapping stain distribution in pathology slides using whole slide imaging αEβ7 Integrin Identifies Subsets of Pro-Inflammatory Colonic CD4+ T Lymphocytes in Ulcerative Colitis.Cdk8 deletion in the Apc(Min) murine tumour model represses EZH2 activity and accelerates tumourigenesis.Computer-based image analysis in breast pathology.A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.Hierarchical nucleus segmentation in digital pathology images.Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection.Image Analysis-Based Approaches for Scoring Mouse Models of Colitis.Glioma Grading Using Cell Nuclei Morphologic Features in Digital Pathology Images.Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.Metastasis detection from whole slide images using local features and random forests.An optimized image analysis algorithm for detecting nuclear signals in digital whole slides for histopathology.Automatic extraction of cell nuclei from H&E-stained histopathological images.Castration-resistant Lgr5(+) cells are long-lived stem cells required for prostatic regeneration.Monitoring and Targeting Anti-VEGF Induced Hypoxia within the Viable Tumor by 19F-MRI and Multispectral Analysis.Combined MEK and ERK inhibition overcomes therapy-mediated pathway reactivation in RAS mutant tumors.Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images.Automatic cellularity assessment from post-treated breast surgical specimens.An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival.Segmentation of clustered cells in negative phase contrast images with integrated light intensity and cell shape information.Effects of different preprocessing algorithms on the prognostic value of breast tumour microscopic images.Using cell nuclei features to detect colon cancer tissue in hematoxylin and eosin stained slides.Imprint cytology-based breast malignancy screening: an efficient nuclei segmentation technique.CD8+ T cell infiltration in breast and colon cancer: A histologic and statistical analysis.Feature-Based Representation Improves Color Decomposition and Nuclear Detection Using a Convolutional Neural Network.A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.A Kinect-Based Segmentation of Touching-Pigs for Real-Time Monitoring.Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images

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P2860

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

http://www.wikidata.org/entity/Q34906509

description

2013 nî lūn-bûn

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2013 թուականի Յուլիսին հրատարակուած գիտական յօդուած

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2013 թվականի հուլիսին հրատարակված գիտական հոդված

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2013年の論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年论文

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name

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

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Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

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Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@nl

type

label

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@ast

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@en

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@nl

prefLabel

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@ast

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@en

Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

@nl

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Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

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André Huisman

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Josien P W Pluim

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Max A Viergever

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Mitko Veta

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Paul J van Diest

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Robert Kornegoor

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P2860

Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up

Histopathological image analysis: a review

How to measure image quality in tissue-based diagnosis (diagnostic surgical pathology).

RNAi microarray analysis in cultured mammalian cells.

Image standards in tissue-based diagnosis (diagnostic surgical pathology)

Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer.

Learning regions of interest from low level maps in virtual microscopy

Towards a computer aided diagnosis system dedicated to virtual microscopy based on stereology sampling and diffusion maps

A supervised visual model for finding regions of interest in basal cell carcinoma images.

Computer-aided detection of centroblasts for follicular lymphoma grading using adaptive likelihood-based cell segmentation.

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