The collection, management, exchange, and interpretation of pathology knowledge — including slides and data — in a digital environment is referred to as digital pathology. When glass slides are scanned with a scanning device, a high-resolution digital image is generated that can be viewed on a computer screen or mobile device. It is possible to image an entire glass slide under bright field or fluorescent conditions at a magnification equivalent to microscope using high-throughput, automated optical pathology scanners. Using advanced automated pathology software systems, digital slides may be shared over networks. To help in the interpretation and quantification of biomarker expression within tissue sections, automated image analysis tools can be used. The rapid advancement of whole-slide imaging (WSI) technology, as well as advancements in software applications, LIS/LIMS interfacing, and high-speed networking, has enabled pathologists to completely incorporate digital pathology into their workflows. Pathologists can interact, analyse, and communicate with ease and accuracy using digital pathology, resulting in increased efficiency and productivity. Enhanced translational testing, computer assisted diagnosis (CAD), and personalised medicine may all be part of the future of digital pathology. Large biopharmaceuticals and top clinical research organisations (CROs) are rapidly using digital pathology to streamline drug development processes in discovery, pre-clinical, and clinical trials. Digital pathology has the ability to be used for quantitative analysis of new companion diagnostics and novel theranostics in the future. With the emergence of assays that are difficult to distinguish with the naked eye, such as multiplex, or markers that exhibit diffuse staining characteristics across multiple cellular compartments, only one of which may be clinically important, this opportunity may become even more relevant. The increasing complexity of such assays has prompted the creation of digital pathology solutions that combine advanced high-throughput image capture (brightfield, fluorescent, or multispectral) with pattern recognition to morphologically distinguish relevant tissue types and individual cellular compartments, as well as the ability to measure (IHC) staining strength. This is contributing to the development of digital pathology systems that compare sample analysis performance to a standard curve derived from clinical data to provide a clinically appropriate diagnostic or prognostic score. Those who are interested to publish their article in our journal, they can submit it either send it as an email attachment to this below given mail id or submit it online through given link: https://www.longdom.org/submissions/medical-surgical-pathology.html

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John Robert

Journal of Medical and Surgical Pathology

Email: surgpathology@emedsci.com

ISSN: 2472-4971 | NLM ID: 101245791