AI Medical Compendium Topic

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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...

Rethinking ImageNet Pre-training for Computational Histopathology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Transfer learning from ImageNet pretrained weights is widely used when training Deep Learning models on a Histopathology dataset. However, the visual features of the two domains are different. Rather than ImageNet pretrained weights, pre-training on ...

A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Multiplexed immunofluorescence provides an un-precedented opportunity for studying specific cell-to-cell and cell microenvironment interactions. We employ graph neural networks to combine features obtained from tissue morphology with measurements of ...

Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach.

World journal of gastroenterology
BACKGROUND: Studies correlating specific genetic mutations and treatment response are ongoing to establish an effective treatment strategy for gastric cancer (GC). To facilitate this research, a cost- and time-effective method to analyze the mutation...

A Deep Learning-Based Approach for Glomeruli Instance Segmentation from Multistained Renal Biopsy Pathologic Images.

The American journal of pathology
Glomeruli instance segmentation from pathologic images is a fundamental step in the automatic analysis of renal biopsies. Glomerular histologic manifestations vary widely among diseases and cases, and several special staining methods are necessary fo...

Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.

The Lancet. Oncology
BACKGROUND: Detecting microsatellite instability (MSI) in colorectal cancer is crucial for clinical decision making, as it identifies patients with differential treatment response and prognosis. Universal MSI testing is recommended, but many patients...

Deep Learning for Virtual Histological Staining of Bright-Field Microscopic Images of Unlabeled Carotid Artery Tissue.

Molecular imaging and biology
PURPOSE: Histological analysis of artery tissue samples is a widely used method for diagnosis and quantification of cardiovascular diseases. However, the variable and labor-intensive tissue staining procedures hinder efficient and informative histolo...

Classification of Histologic Images Using a Single Staining: Experiments with Deep Learning on Deconvolved Images.

Studies in health technology and informatics
The automated analysis of digitized immunohistochemistry microscope slides is usually a challenging task, because markers should be analysed on the tumor area only. Tumor areas could be recognized on a different slide, stained with Haematoxylin-Eosin...

Artificial Intelligence Will Not Replace Health Professionals, but the Proper Use of Artificial Intelligence Will Make Health Professionals Better.

Cancer research
Deep learning has enabled great advances to be made in cancer research with regards to diagnosis, prognosis, and treatment. The study by Wang and colleagues in this issue of develops a deep learning algorithm with the ability to digitally stain hist...