Literature DB >> 23157334

Digital imaging in pathology: whole-slide imaging and beyond.

Farzad Ghaznavi1, Andrew Evans, Anant Madabhushi, Michael Feldman.   

Abstract

Digital imaging in pathology has undergone an exponential period of growth and expansion catalyzed by changes in imaging hardware and gains in computational processing. Today, digitization of entire glass slides at near the optical resolution limits of light can occur in 60 s. Whole slides can be imaged in fluorescence or by use of multispectral imaging systems. Computational algorithms have been developed for cytometric analysis of cells and proteins in subcellular locations by use of multiplexed antibody staining protocols. Digital imaging is unlocking the potential to integrate primary image features into high-dimensional genomic assays by moving microscopic analysis into the digital age. This review highlights the emerging field of digital pathology and explores the methods and analytic approaches being developed for the application and use of these methods in clinical care and research settings.

Mesh:

Year:  2012        PMID: 23157334     DOI: 10.1146/annurev-pathol-011811-120902

Source DB:  PubMed          Journal:  Annu Rev Pathol        ISSN: 1553-4006            Impact factor:   23.472


  92 in total

1.  Use of Digital Whole Slide Imaging in Dermatopathology.

Authors:  Tracy Onega; Lisa M Reisch; Paul D Frederick; Berta M Geller; Heidi D Nelson; Jason P Lott; Andrea C Radick; David E Elder; Raymond L Barnhill; Michael W Piepkorn; Joann G Elmore
Journal:  J Digit Imaging       Date:  2016-04       Impact factor: 4.056

2.  Improving Classification of Breast Cancer by Utilizing the Image Pyramids of Whole-Slide Imaging and Multi-Scale Convolutional Neural Networks.

Authors:  Li Tong; Ying Sha; May D Wang
Journal:  Proc COMPSAC       Date:  2019-07-09

Review 3.  Review of Telemicrobiology.

Authors:  Daniel D Rhoads; Blaine A Mathison; Henry S Bishop; Alexandre J da Silva; Liron Pantanowitz
Journal:  Arch Pathol Lab Med       Date:  2015-08-28       Impact factor: 5.534

Review 4.  Computer-Aided Histopathological Image Analysis Techniques for Automated Nuclear Atypia Scoring of Breast Cancer: a Review.

Authors:  Asha Das; Madhu S Nair; S David Peter
Journal:  J Digit Imaging       Date:  2020-10       Impact factor: 4.056

5.  Staining correction in digital pathology by utilizing a dye amount table.

Authors:  Pinky A Bautista; Yukako Yagi
Journal:  J Digit Imaging       Date:  2015-06       Impact factor: 4.056

6.  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

7.  Whole tumor section quantitative image analysis maximizes between-pathologists' reproducibility for clinical immunohistochemistry-based biomarkers.

Authors:  Michael Barnes; Chukka Srinivas; Isaac Bai; Judith Frederick; Wendy Liu; Anindya Sarkar; Xiuzhong Wang; Yao Nie; Bryce Portier; Monesh Kapadia; Olcay Sertel; Elizabeth Little; Bikash Sabata; Jim Ranger-Moore
Journal:  Lab Invest       Date:  2017-08-14       Impact factor: 5.662

8.  Presence of tumour high-endothelial venules is an independent positive prognostic factor and stratifies patients with advanced-stage oral squamous cell carcinoma.

Authors:  Anna M Wirsing; Oddveig G Rikardsen; Sonja E Steigen; Lars Uhlin-Hansen; Elin Hadler-Olsen
Journal:  Tumour Biol       Date:  2015-09-17

Review 9.  Review of quantitative multiscale imaging of breast cancer.

Authors:  Michael A Pinkert; Lonie R Salkowski; Patricia J Keely; Timothy J Hall; Walter F Block; Kevin W Eliceiri
Journal:  J Med Imaging (Bellingham)       Date:  2018-01-22

10.  Accuracy of Digital Pathologic Analysis vs Traditional Microscopy in the Interpretation of Melanocytic Lesions.

Authors:  Tracy Onega; Raymond L Barnhill; Michael W Piepkorn; Gary M Longton; David E Elder; Martin A Weinstock; Stevan R Knezevich; Lisa M Reisch; Patricia A Carney; Heidi D Nelson; Andrea C Radick; Joann G Elmore
Journal:  JAMA Dermatol       Date:  2018-10-01       Impact factor: 10.282

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