Technologie des lames virtuelles

Ameisen, David; Naour, Gwenola Le; Daniel, Christel

doi:10.1051/medsci/20122811017

Cited by 9 publications

(3 citation statements)

References 22 publications

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“…Alternatively, whole-slide scanners provide a high-speed standardized acquisition with predefined parameters, with the ability to image up to 200 slides in one night, in bright field or with fluorescence, at 20 or 40× (Weinstein et al, 2009 ; Nederlof et al, 2011 ; Pantanowitz et al, 2011 ; Ameisen et al, 2012 ; Laurent et al, 2013 ; Gallas et al, 2014 ). A recent example of the use of whole-slide scanners is the BigBrain: a whole human brain scanned at 20 μm resolution (Amunts et al, 2013 ).…”

Section: Novel Techniques and Perspectivesmentioning

confidence: 99%

Axon and Myelin Morphology in Animal and Human Spinal Cord

et al. 2017

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Characterizing precisely the microstructure of axons, their density, size and myelination is of interest for the neuroscientific community, for example to help maximize the outcome of studies on white matter (WM) pathologies of the spinal cord (SC). The existence of a comprehensive and structured database of axonal measurements in healthy and disease models could help the validation of results obtained by different researchers. The purpose of this article is to provide such a database of healthy SC WM, to discuss the potential sources of variability and to suggest avenues for robust and accurate quantification of axon morphometry based on novel acquisition and processing techniques. The article is organized in three sections. The first section reviews morphometric results across species according to range of densities and counts of myelinated axons, axon diameter and myelin thickness, and characteristics of unmyelinated axons in different regions. The second section discusses the sources of variability across studies, such as age, sex, spinal pathways, spinal levels, statistical power and terminology in regard to tracts and protocols. The third section presents new techniques and perspectives that could benefit histology studies. For example, coherent anti-stokes Raman spectroscopy (CARS) imaging can provide sub-micrometric resolution without the need for fixation and staining, while slide scanners and stitching algorithms can provide full cross-sectional area of SC. In combination with these acquisition techniques, automatic segmentation algorithms for delineating axons and myelin sheath can help provide large-scale statistics on axon morphometry.

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Section: Novel Techniques and Perspectivesmentioning

confidence: 99%

Axon and Myelin Morphology in Animal and Human Spinal Cord

et al. 2017

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“…The applications of WSI are tremendous, but, currently, the primary utilization of the technique is for transmission of digital images, second opinion consultation [5], quality assurance [6], teaching [7] and research [8], remote frozen section diagnosis [5], proficiency testing [6], multicenter research [5], and archiving [9]. The high resolution of digital images along with the refinement of technology could now allow for WSI to be used as an alternative to conventional microscopy (CM) [10].…”

Section: Introductionmentioning

confidence: 99%

Image Montaging for Creating a Virtual Pathology Slide: An Innovative and Economical Tool to Obtain a Whole Slide Image

Banavar

Chippagiri

Pandurangappa

et al. 2016

Analytical Cellular Pathology

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Background. Microscopes are omnipresent throughout the field of biological research. With microscopes one can see in detail what is going on at the cellular level in tissues. Though it is a ubiquitous tool, the limitation is that with high magnification there is a small field of view. It is often advantageous to see an entire sample at high magnification. Over the years technological advancements in optics have helped to provide solutions to this limitation of microscopes by creating the so-called dedicated “slide scanners” which can provide a “whole slide digital image.” These scanners can provide seamless, large-field-of-view, high resolution image of entire tissue section. The only disadvantage of such complete slide imaging system is its outrageous cost, thereby hindering their practical use by most laboratories, especially in developing and low resource countries. Methods. In a quest for their substitute, we tried commonly used image editing software Adobe Photoshop along with a basic image capturing device attached to a trinocular microscope to create a digital pathology slide. Results. The seamless image created using Adobe Photoshop maintained its diagnostic quality. Conclusion. With time and effort photomicrographs obtained from a basic camera-microscope set up can be combined and merged in Adobe Photoshop to create a whole slide digital image of practically usable quality at a negligible cost.

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“…Training allows the CNN to learn filter values. AI/deep learning integration in pathology and histology was introduced with advances in digital imaging (Brachtel & Yagi, 2012;Ghaznavi, Evans, Madabhushi, & Feldman, 2013;Gurcan et al, 2009;Aeffner et al, 2019;Ameisen, Naour, & Daniel, 2012;Bhargava & Madabhushi, 2016;Hanna et al, 2019;Webster & Dunstan, 2014;Ying & Monticello, 2006;Zarella et al, 2019;Laurinavicius et al, 2012;Pantanowitz, 2010;Park, Pantanowitz, & Parwani, 2012).…”

mentioning

confidence: 99%

Quantitative neurotoxicology: Potential role of artificial intelligence/deep learning approach

Srivastava

Hanig

2020

J of Applied Toxicology

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Neurotoxicity studies are important in the preclinical stages of drug development process, because exposure to certain compounds that may enter the brain across a permeable blood brain barrier damages neurons and other supporting cells such as astrocytes. This could, in turn, lead to various neurological disorders such as Parkinson's or Huntington's disease as well as various dementias. Toxicity assessment is often done by pathologists after these exposures by qualitatively or semiquantitatively grading the severity of neurotoxicity in histopathology slides. Quantification of the extent of neurotoxicity supports qualitative histopathological analysis and provides a better understanding of the global extent of brain damage. Stereological techniques such as the utilization of an optical fractionator provide an unbiased quantification of the neuronal damage; however, the process is time‐consuming. Advent of whole slide imaging (WSI) introduced digital image analysis which made quantification of neurotoxicity automated, faster and with reduced bias, making statistical comparisons possible. Although automated to a certain level, simple digital image analysis requires manual efforts of experts which is time‐consuming and limits analysis of large datasets. Digital image analysis coupled with a deep learning artificial intelligence model provides a good alternative solution to time‐consuming stereological and simple digital analysis. Deep learning models could be trained to identify damaged or dead neurons in an automated fashion. This review has focused on and discusses studies demonstrating the role of deep learning in segmentation of brain regions, toxicity detection and quantification of degenerated neurons as well as the estimation of area/volume of degeneration.

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Technologie des lames virtuelles

Cited by 9 publications

References 22 publications

Axon and Myelin Morphology in Animal and Human Spinal Cord

Axon and Myelin Morphology in Animal and Human Spinal Cord

Image Montaging for Creating a Virtual Pathology Slide: An Innovative and Economical Tool to Obtain a Whole Slide Image

Quantitative neurotoxicology: Potential role of artificial intelligence/deep learning approach

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