AIMC Topic: Staining and Labeling

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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...

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

BMC cancer
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...

MuDeRN: Multi-category classification of breast histopathological image using deep residual networks.

Artificial intelligence in medicine
MOTIVATION: Identifying carcinoma subtype can help to select appropriate treatment options and determining the subtype of benign lesions can be beneficial to estimate the patients' risk of developing cancer in the future. Pathologists' assessment of ...

Automated Preparation of MS-Sensitive Fluorescently Labeled N-Glycans with a Commercial Pipetting Robot.

SLAS technology
N-Glycan analysis is routinely performed for biotherapeutic protein characterization. A recently introduced N-glycan analysis kit using RapiFluor-MS (RFMS) labeling provides time savings over reductive amination labeling methods while also providing ...

Image analysis and machine learning for detecting malaria.

Translational research : the journal of laboratory and clinical medicine
Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts a...

MIAQuant, a novel system for automatic segmentation, measurement, and localization comparison of different biomarkers from serialized histological slices.

European journal of histochemistry : EJH
In the clinical practice, automatic image analysis methods quickly quantizing histological results by objective and replicable methods are getting more and more necessary and widespread. Despite several commercial software products are available for ...

Image based Machine Learning for identification of macrophage subsets.

Scientific reports
Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplif...

A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology.

IEEE transactions on medical imaging
Nuclear segmentation in digital microscopic tissue images can enable extraction of high-quality features for nuclear morphometrics and other analysis in computational pathology. Conventional image processing techniques, such as Otsu thresholding and ...

Anticancer activity of biologically synthesized silver and gold nanoparticles on mouse myoblast cancer cells and their toxicity against embryonic zebrafish.

Materials science & engineering. C, Materials for biological applications
The aim of this study was to evaluate the anticancer activity of bioinspired silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) against mouse myoblast cancer cells (CC). Both AgNPs and AuNPs were biologically synthesized using Spinacia olera...