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Immunohistochemistry

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Deep Semi Supervised Generative Learning for Automated Tumor Proportion Scoring on NSCLC Tissue Needle Biopsies.

Scientific reports
The level of PD-L1 expression in immunohistochemistry (IHC) assays is a key biomarker for the identification of Non-Small-Cell-Lung-Cancer (NSCLC) patients that may respond to anti PD-1/PD-L1 treatments. The quantification of PD-L1 expression current...

Heterogeneous Domain Adaptation for IHC Classification of Breast Cancer Subtypes.

IEEE/ACM transactions on computational biology and bioinformatics
Increasingly, multiple parallel omics datasets are collected from biological samples. Integrating these datasets for classification is an open area of research. Additionally, whilst multiple datasets may be available for the training samples, future ...

An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA.

IEEE transactions on medical imaging
One of the methods for stratifying different molecular classes of breast cancer is the Nottingham prognostic index plus, which uses breast cancer relevant biomarkers to stain tumor tissues prepared on tissue microarray (TMA). To determine the molecul...

Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Clinical cancer research : an official journal of the American Association for Cancer Research
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...

Segmentation of glandular epithelium in colorectal tumours to automatically compartmentalise IHC biomarker quantification: A deep learning approach.

Medical image analysis
In this paper, we propose a method for automatically annotating slide images from colorectal tissue samples. Our objective is to segment glandular epithelium in histological images from tissue slides submitted to different staining techniques, includ...

Automated extraction of Biomarker information from pathology reports.

BMC medical informatics and decision making
BACKGROUND: Pathology reports are written in free-text form, which precludes efficient data gathering. We aimed to overcome this limitation and design an automated system for extracting biomarker profiles from accumulated pathology reports.

Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images.

PloS one
In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a trained pathologist using a manual method, which consists of counting e...

Automatic labeling of molecular biomarkers of immunohistochemistry images using fully convolutional networks.

PloS one
This paper addresses the problem of quantifying biomarkers in multi-stained tissues based on the color and spatial information of microscopy images of the tissue. A deep learning-based method that can automatically localize and quantify the regions e...

Overexpression of EMMPRIN is associated with lymph node metastasis and advanced stage of non-small cell lung cancer: a retrospective study.

BMC pulmonary medicine
BACKGROUND: Previous studies show that overexpression of EMMPRIN involved in the malignant biological behavior of tumors. This investigation was to disclose the expression status of EMMPRIN in non-small cell lung cancer (NSCLC) and its clinical value...