AIMC Topic: Staining and Labeling

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Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 20, 2023
Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized glass slide, called Whole Slide Image (WSI), for further examination. These procedures frequently int...
Neural Networks, Computer Normal Distribution Uncertainty Artifacts Staining and Labeling
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Deep-learning-based cross-modality translation from Stokes image to bright-field contrast.

Journal of biomedical optics Oct 20, 2023
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...
Microscopy Liver Deep Learning Staining and Labeling Image Processing, Computer-Assisted Lung
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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 Aug 7, 2023
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...
Humans Retrospective Studies Pilot Projects Staining and Labeling Deep Learning Colorectal Neoplasms Rectal Neoplasms Colonic Neoplasms
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Automatic normalized digital color staining in the recognition of abnormal blood cells using generative adversarial networks.

Computer methods and programs in biomedicine May 30, 2023
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...
Blood Cells Image Processing, Computer-Assisted Leukocytes Staining and Labeling Neural Networks, Computer
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Comparison of deep learning models for digital H&E staining from unpaired label-free multispectral microscopy images.

Computer methods and programs in biomedicine Apr 5, 2023
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...
Eosine Yellowish-(YS) Microscopy Image Processing, Computer-Assisted Staining and Labeling Deep Learning
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Phase Contrast Image Restoration by Formulating Its Imaging Principle and Reversing the Formulation With Deep Neural Networks.

IEEE transactions on medical imaging Apr 3, 2023
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...
Microscopy, Phase-Contrast Artifacts Staining and Labeling Neural Networks, Computer
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Classification of HEp-2 Staining Pattern Images Using Adapted Multilayer Perceptron Neural Network-Based Intra-Class Variation of Cell Shape.

Sensors (Basel, Switzerland) Feb 15, 2023
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...
Staining and Labeling Cell Shape Probability Neural Networks, Computer
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Virtual tissue staining in pathology using machine learning.

Expert review of molecular diagnostics Nov 29, 2022
Machine Learning Staining and Labeling Humans
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Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer.

Nature communications Nov 8, 2022
Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomarker for immunotherapies. The cost, time, and variability of PD-L1 quantification by immunohistochemistry (IHC) are a challenge. In contrast, hematoxyl...
Breast Neoplasms Biomarkers, Tumor Female Lung Neoplasms B7-H1 Antigen Deep Learning Humans Hematoxylin Staining and Labeling
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Deep learning-assisted co-registration of full-spectral autofluorescence lifetime microscopic images with H&E-stained histology images.

Communications biology Oct 21, 2022
Autofluorescence lifetime images reveal unique characteristics of endogenous fluorescence in biological samples. Comprehensive understanding and clinical diagnosis rely on co-registration with the gold standard, histology images, which is extremely c...
Staining and Labeling Deep Learning
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