AIMC Topic: Coloring Agents

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Boundary-aware glomerulus segmentation: Toward one-to-many stain generalization.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The growing availability of scanned whole-slide images (WSIs) has allowed nephropathology to open new possibilities for medical decision-making over high-resolution images. Diagnosis of renal WSIs includes locating and identifying specific structures...

MVFStain: Multiple virtual functional stain histopathology images generation based on specific domain mapping.

Medical image analysis
To the best of our knowledge, artificial intelligence stain generation is an urgent requirement for histopathology images. Pathological examinations usually only utilize hematoxylin and eosin (H&E) regular staining to show histomorphological characte...

Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes?

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this article, we provide a convenient tool for all researchers to predict the value of the molar absorption coefficient for a wide number of dyes without any computer costs. The new model is based on RFR method (ALogPS, OEstate + Fragmentor + QNPR...

Automated stain-free histomorphometry of peripheral nerve by contrast-enhancing techniques and artificial intelligence.

Journal of neuroscience methods
BACKGROUND: Traditional histopathologic evaluation of peripheral nerve using brightfield microscopy is resource-intensive, necessitating complex sample preparation. Label-free imaging techniques paired with artificial intelligence-based image reconst...

A deep learning-driven low-power, accurate, and portable platform for rapid detection of COVID-19 using reverse-transcription loop-mediated isothermal amplification.

Scientific reports
This paper presents a deep learning-driven portable, accurate, low-cost, and easy-to-use device to perform Reverse-Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) to facilitate rapid detection of COVID-19. The 3D-printed device-powered...

Stain-free detection of embryo polarization using deep learning.

Scientific reports
Polarization of the mammalian embryo at the right developmental time is critical for its development to term and would be valuable in assessing the potential of human embryos. However, tracking polarization requires invasive fluorescence staining, im...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Scientific reports
Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires ...

Deep learning-based transformation of H&E stained tissues into special stains.

Nature communications
Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly used, special stains can provide additional contrast to different tissue components. Here, we demonstra...

Automated identification of glomeruli and synchronised review of special stains in renal biopsies by machine learning and slide registration: a cross-institutional study.

Histopathology
AIMS: Machine learning in digital pathology can improve efficiency and accuracy via prescreening with automated feature identification. Studies using uniform histological material have shown promise. Generalised application requires validation on sli...

Learning the Exciton Properties of Azo-dyes.

The journal of physical chemistry letters
The determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine lear...