Pathology Imaging
Pathology Imaging - Related Videos
04:14
Expansion Pathology: A Method for High-resolution Optical Imaging of Clinical Tissue Samples
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2023
In this video, we describe a method called expansion pathology, a variant of expansion microscopy, wherein the clinical tissue specimens are chemically expanded using a polymer network for microscopic examination of nanoscale structures.
11:05
High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
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Cited by 30 •
2015
Fourier Transform Infrared (FT-IR) spectroscopic imaging is a fast and label-free approach to obtain biochemical data sets of cells and tissues. Here, we demonstrate how to obtain high-definition FT-IR images of tissue sections towards improving disease diagnosis.
09:01
Non-invasive Assessment of the Efficacy of New Therapeutics for Intestinal Pathologies Using Serial Endoscopic Imaging of Live Mice
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Cited by 9 •
2015
We describe methods for longitudinal monitoring of the efficacy of therapeutics for the treatment of colonic pathologies in mice using a rigid endoscope. This protocol can be readily used for the characterization of the therapeutic response of an individual tumor in live mice and also for monitoring potential disease relapse.
09:04
In Vivo Tracking of Edema Development and Microvascular Pathology in a Model of Experimental Cerebral Malaria Using Magnetic Resonance Imaging
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Cited by 7 •
2017
We describe a mouse model of experimental cerebral malaria and show how inflammatory and microvascular pathology can be tracked in vivo using magnetic resonance imaging.
05:33
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Cited by 1 •
2025
Integrated image management, artificial intelligence (AI), and reporting systems have revolutionized diagnostic pathology practice. In this paper, we introduce FlexLIS, a state-of-the-art system that enables AI to assist pathologists in performing histopathology image assessments and generating diagnostic reports.
FAQs
Contrast and staining make cellular and tissue features easier to distinguish from their surroundings. During Pathology Imaging, these visual differences help reveal normal architecture and structural abnormalities that may be difficult to recognize without enhancement. The resulting image can therefore support interpretation of disease-associated changes, including patterns used for diagnosis, tumor classification, and grading.
These approaches provide different routes for examining prepared material. Light microscopy and fluorescence support microscopic visualization, while digital scanning enables whole-slide review in a digital format. That distinction matters because digital images can be shared, measured quantitatively, and processed computationally, whereas microscopy-based examination centers on viewing the specimen through the selected imaging modality.
Image analysis turns visual observations into measurements or computationally derived patterns. It can help distinguish normal architecture from abnormal features and support quantitative assessment rather than relying only on descriptive review. In research, these analyses contribute to biomarker investigation and studies of disease mechanisms; in clinical contexts, they can support classification, grading, and treatment-response assessment.
Preparing cells, tissues, or organs creates the material that can be examined by microscopy or digital scanning. The quality and organization of that preparation influence how clearly structural features appear, which affects comparison between normal architecture and disease-associated changes. Careful preparation therefore supports reliable visual interpretation and the downstream analyses used in medical pathology.
A typical workflow begins with specimen preparation, followed by image acquisition using light microscopy, fluorescence, or digital scanning. Contrast and staining then help separate relevant structures from surrounding tissue, after which the image can be reviewed or analyzed. Depending on the purpose, the workflow may produce a diagnostic interpretation, quantitative measurement, disease grade, or treatment-response assessment.
They are especially useful when visual structural evidence is needed to identify disease, classify a tumor, assign a disease grade, or assess whether treatment has produced a response. These uses connect microscopic or digitally scanned findings with clinically meaningful interpretation. Pathology Imaging therefore contributes across diagnostic evaluation and follow-up, rather than serving only as a research visualization tool.
Digital pathology enables whole-slide review, quantitative measurements, data sharing, and computational analysis. These capabilities can improve consistency between assessments and make image-based information easier to use across clinical and research settings. They also support investigation of biomarkers and disease mechanisms, while contributing to personalized care by connecting image findings with broader analyses of disease and treatment.