2018
DOI: 10.4103/jpi.jpi_69_18
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Twenty Years of Digital Pathology: An Overview of the Road Travelled, What is on the Horizon, and the Emergence of Vendor-Neutral Archives

Abstract: Almost 20 years have passed since the commercial introduction of whole-slide imaging (WSI) scanners. During this time, the creation of various WSI devices with the ability to digitize an entire glass slide has transformed the field of pathology. Parallel advances in computational technology and storage have permitted rapid processing of large-scale WSI datasets. This article provides an overview of important past and present efforts related to WSI. An account of how the virtual microscope evolved from the need… Show more

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Cited by 169 publications
(127 citation statements)
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“…MENNDL tailors the network design and hyperparameters of the network for a given dataset, automating and accelerating a process that is typically done manually by scientists for each individual dataset. Pathology deep learning applications have been rapidly emerging; examples include pathology classification, tumor segmentation, and semantic segmentation of cell nuclei [31], [32], [33]. We anticipate that MENNDL-generated networks are likely to be of great value for these applications.…”
Section: Resultsmentioning
confidence: 99%
“…MENNDL tailors the network design and hyperparameters of the network for a given dataset, automating and accelerating a process that is typically done manually by scientists for each individual dataset. Pathology deep learning applications have been rapidly emerging; examples include pathology classification, tumor segmentation, and semantic segmentation of cell nuclei [31], [32], [33]. We anticipate that MENNDL-generated networks are likely to be of great value for these applications.…”
Section: Resultsmentioning
confidence: 99%
“…Advances in computational technology and data storage make it possible to rapidly generate a large number of WSI datasets. As a result, computational pathology, which handles and analyzes digitized image data, has come under the spotlight in the field of pathological research . Several studies conducted recently using WSI are now described.…”
Section: Future Perspectivesmentioning
confidence: 99%
“…As a result, computational pathology, which handles and analyzes digitized image data, has come under the spotlight in the field of pathological research. 130 Several studies conducted recently using WSI are now described. The grading of HCC based on nuclear texture analysis of WSI has been reported.…”
Section: Computational Pathology In Hccmentioning
confidence: 99%
“…Recently, pathologists have started to leverage machine learning to accelerate pattern recognition from histologic data and potentially extract deeper diagnostic insight. Digital analysis of histological specimens first became possible with the introduction of bright-field WSI instruments twenty years ago 16,17 , but it was not until 2016 that the FDA released guidance on the technical requirements for use of digital imaging in diagnosis 18 (Figure 1). Digital pathology has experienced dramatic growth in the past few years fueled in large part by the development of machine learning algorithms capable of assisting in the interpretation of H&E stained slides, which histopathology services must process in very high volume (often >1 million slides per year in a single hospital).…”
Section: Tissue Imaging In a Clinical Settingmentioning
confidence: 99%