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Staining and Labeling

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[Express-diagnosis of the diseases of the eye and its appendages by scanning electron microscopy with supravital staining].

Vestnik oftalmologii
This review describes the history of development of a new line of chemical reagents that prompts to significantly reevaluate the application of scanning electron microscopy (SEM) in medical and biological studies, particularly in ophthalmology; consi...

Classification of HEp-2 Staining Pattern Images Using Adapted Multilayer Perceptron Neural Network-Based Intra-Class Variation of Cell Shape.

Sensors (Basel, Switzerland)
There exists a growing interest from the clinical practice research communities in the development of methods to automate HEp-2 stained cells classification procedure from histopathological images. Challenges faced by these methods include variations...

Comparison of deep learning models for digital H&E staining from unpaired label-free multispectral microscopy images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This paper presents the quantitative comparison of three generative models of digital staining, also known as virtual staining, in H&E modality (i.e., Hematoxylin and Eosin) that are applied to 5 types of breast tissue. More...

Phase Contrast Image Restoration by Formulating Its Imaging Principle and Reversing the Formulation With Deep Neural Networks.

IEEE transactions on medical imaging
Phase contrast microscopy, as a noninvasive imaging technique, has been widely used to monitor the behavior of transparent cells without staining or altering them. Due to the optical principle of the specifically-designed microscope, phase contrast m...

Automatic normalized digital color staining in the recognition of abnormal blood cells using generative adversarial networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Combining knowledge of clinical pathologists and deep learning models is a growing trend in morphological analysis of cells circulating in blood to add objectivity, accuracy, and speed in diagnosing hematological and non-he...

Deep learning for the prediction of the chemotherapy response of metastatic colorectal cancer: comparing and combining H&E staining histopathology and infrared spectral histopathology.

The Analyst
Colorectal cancer is a global public health problem with one of the highest death rates. It is the second most deadly type of cancer and the third most frequently diagnosed in the world. The present study focused on metastatic colorectal cancer (mCRC...

[Application of Deep Learning Algorithm in the Grading Assessment of Corneal Fluorescein Staining].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To explore the application value of applying deep learning (DL) algorithm in the grading assessment of corneal fluorescein staining.

Deep-learning-based cross-modality translation from Stokes image to bright-field contrast.

Journal of biomedical optics
SIGNIFICANCE: Mueller matrix (MM) microscopy has proven to be a powerful tool for probing microstructural characteristics of biological samples down to subwavelength scale. However, in clinical practice, doctors usually rely on bright-field microscop...

A Laplacian Pyramid Based Generative H&E Stain Augmentation Network.

IEEE transactions on medical imaging
Hematoxylin and Eosin (H&E) staining is a widely used sample preparation procedure for enhancing the saturation of tissue sections and the contrast between nuclei and cytoplasm in histology images for medical diagnostics. However, various factors, su...