Literature DB >> 28578626

The Pathologist 2.0: An Update on Digital Pathology in Veterinary Medicine.

Christof A Bertram1, Robert Klopfleisch1.   

Abstract

Using light microscopy to describe the microarchitecture of normal and diseased tissues has changed very little since the middle of the 19th century. While the premise of histologic analysis remains intact, our relationship with the microscope is changing dramatically. Digital pathology offers new forms of visualization, and delivery of images is facilitated in unprecedented ways. This new technology can untether us entirely from our light microscopes, with many pathologists already performing their jobs using virtual microscopy. Several veterinary colleges have integrated virtual microscopy in their curriculum, and some diagnostic histopathology labs are switching to virtual microscopy as their main tool for the assessment of histologic specimens. Considering recent technical advancements of slide scanner and viewing software, digital pathology should now be considered a serious alternative to traditional light microscopy. This review therefore intends to give an overview of the current digital pathology technologies and their potential in all fields of veterinary pathology (ie, research, diagnostic service, and education). A future integration of digital pathology in the veterinary pathologist's workflow seems to be inevitable, and therefore it is proposed that trainees should be taught in digital pathology to keep up with the unavoidable digitization of the profession.

Keywords:  automated image analysis; digital microscopy; review; slide scanner; tele-education; telediagnosis; telepathology; virtual microscopy; whole-slide imaging; workstation

Mesh:

Year:  2017        PMID: 28578626     DOI: 10.1177/0300985817709888

Source DB:  PubMed          Journal:  Vet Pathol        ISSN: 0300-9858            Impact factor:   2.221


  13 in total

1.  Digital Microscopy, Image Analysis, and Virtual Slide Repository.

Authors:  Famke Aeffner; Hibret A Adissu; Michael C Boyle; Robert D Cardiff; Erik Hagendorn; Mark J Hoenerhoff; Robert Klopfleisch; Susan Newbigging; Dirk Schaudien; Oliver Turner; Kristin Wilson
Journal:  ILAR J       Date:  2018-12-01

2.  Digital pathology in academia: Implementation and impact.

Authors:  Yava Jones-Hall
Journal:  Lab Anim (NY)       Date:  2021-08-04       Impact factor: 12.625

Review 3.  Approaches to Evaluate Lung Inflammation in Translational Research.

Authors:  David K Meyerholz; Jessica C Sieren; Amanda P Beck; Heather A Flaherty
Journal:  Vet Pathol       Date:  2017-08-16       Impact factor: 2.221

4.  Artificial Intelligence-Assisted Image Analysis of Acetaminophen-Induced Acute Hepatic Injury in Sprague-Dawley Rats.

Authors:  Eun Bok Baek; Ji-Hee Hwang; Heejin Park; Byoung-Seok Lee; Hwa-Young Son; Yong-Bum Kim; Sang-Yeop Jun; Jun Her; Jaeku Lee; Jae-Woo Cho
Journal:  Diagnostics (Basel)       Date:  2022-06-16

5.  Editorial: On continuing to educate during these times.

Authors:  Carrie M Johnson; Richard A Prayson
Journal:  Ann Diagn Pathol       Date:  2020-06-27       Impact factor: 2.090

Review 6.  Contemporary Whole Slide Imaging Devices and Their Applications within the Modern Pathology Department: A Selected Hardware Review.

Authors:  Ankush Patel; Ulysses G J Balis; Jerome Cheng; Zaibo Li; Giovanni Lujan; David S McClintock; Liron Pantanowitz; Anil Parwani
Journal:  J Pathol Inform       Date:  2021-12-09

Review 7.  Validation of digital microscopy: Review of validation methods and sources of bias.

Authors:  Christof A Bertram; Nikolas Stathonikos; Taryn A Donovan; Alexander Bartel; Andrea Fuchs-Baumgartinger; Karoline Lipnik; Paul J van Diest; Federico Bonsembiante; Robert Klopfleisch
Journal:  Vet Pathol       Date:  2021-08-26       Impact factor: 2.221

8.  Cric searchable image database as a public platform for conventional pap smear cytology data.

Authors:  Mariana T Rezende; Raniere Silva; Fagner de O Bernardo; Alessandra H G Tobias; Paulo H C Oliveira; Tales M Machado; Caio S Costa; Fatima N S Medeiros; Daniela M Ushizima; Claudia M Carneiro; Andrea G C Bianchi
Journal:  Sci Data       Date:  2021-06-10       Impact factor: 6.444

9.  Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis.

Authors:  Niek Andresen; Manuel Wöllhaf; Katharina Hohlbaum; Lars Lewejohann; Olaf Hellwich; Christa Thöne-Reineke; Vitaly Belik
Journal:  PLoS One       Date:  2020-04-15       Impact factor: 3.240

10.  The Use of Digital Microscopy to Compare the Thicknesses of Normal Corneas and Ex Vivo Rejected Corneal Grafts with a Focus on the Descemet's Membrane.

Authors:  Taíse Tognon; Sabrina Bergeron; Christina Mastromonaco; Kleyton Barella; Adriano Pasqualotti; Laura Nunez; Francisco Murta; Luciene Barbosa de Sousa; Mauro Campos; Miguel Noel Nascentes Burnier
Journal:  J Ophthalmol       Date:  2019-11-15       Impact factor: 1.909

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