Article

Deep Learning-Inferred Multiplex ImmunoFluorescence for IHC Image Quantification

2021-05-02

Abstract excerpt

Reporting biomarkers assessed by routine immunohistochemical (IHC) staining of tissue is broadly used in diagnostic pathology laboratories for patient care. To date, clinical reporting is predominantly qualitative or semi-quantitative. By creating a multitask deep learning framework referred to as DeepLIIF, we present a single-step solution to stain deconvolution/separation, cell segmentation, and quantitative sin...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e914de23-d133-5d31-8eaf-73f8af08de60
DOI: 10.1101/2021.05.01.442219

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep Learning-Inferred Multiplex ImmunoFluorescence for IHC Image QuantificationDOI 10.1101/2021.05.01.442219Read

<i>ROSIE</i> : AI generation of multiplex immunofluorescence staining from histopathology imagesSemantic proximity Read

PixlMap: A generalisable pixel classifier for cellular phenotyping in multiplex immunofluorescence imagesSemantic proximity Read

A deep learning model for molecular label transfer that enables cancer cell identification from histopathology imagesSemantic proximity Read

ImmuNet: A Segmentation-Free Machine Learning Pipeline for Immune Landscape Phenotyping in Tumors by Muliplex ImagingSemantic proximity Read

DigitAb: Domain-Adaptive Cell Type Prediction Method from Light Microscopy ImagesSemantic proximity Read

CPU-READY DEEP LEARNING APPROACH FOR ROBUST TISSUE REGION SEGMENTATION ACROSS MULTI-COHORT H&E AND IHC-STAINED WHOLE SLIDE IMAGESSemantic proximity Read

Dice-XMBD: Deep learning-based cell segmentation for imaging mass cytometrySemantic proximity Read

PhenoBIC: operator-free single-cell spatial phenotyping in multiplex imaging data using deep learning of cell staining patternsSemantic proximity Read

CellBinDB: A Large-Scale Multimodal Annotated Dataset for Cell Segmentation with Benchmarking of Universal ModelsSemantic proximity Read

Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancerSemantic proximity Read

ADSI-MIMO: Adaptive stain imputation with multi-input and multi-output learning for multiplex immunofluorescence imagingSemantic proximity Read

Multiple instance learning on tile level-pathology images provides accurate and interpretable classification for breast cancer molecular subtypesSemantic proximity Read