Literature DB >> 24091812

Whole-slide imaging and automated image analysis: considerations and opportunities in the practice of pathology.

J D Webster1, R W Dunstan.   

Abstract

Digital pathology, the practice of pathology using digitized images of pathologic specimens, has been transformed in recent years by the development of whole-slide imaging systems, which allow for the evaluation and interpretation of digital images of entire histologic sections. Applications of whole-slide imaging include rapid transmission of pathologic data for consultations and collaborations, standardization and distribution of pathologic materials for education, tissue specimen archiving, and image analysis of histologic specimens. Histologic image analysis allows for the acquisition of objective measurements of histomorphologic, histochemical, and immunohistochemical properties of tissue sections, increasing both the quantity and quality of data obtained from histologic assessments. Currently, numerous histologic image analysis software solutions are commercially available. Choosing the appropriate solution is dependent on considerations of the investigative question, computer programming and image analysis expertise, and cost. However, all studies using histologic image analysis require careful consideration of preanalytical variables, such as tissue collection, fixation, and processing, and experimental design, including sample selection, controls, reference standards, and the variables being measured. The fields of digital pathology and histologic image analysis are continuing to evolve, and their potential impact on pathology is still growing. These methodologies will increasingly transform the practice of pathology, allowing it to mature toward a quantitative science. However, this maturation requires pathologists to be at the forefront of the process, ensuring their appropriate application and the validity of their results. Therefore, histologic image analysis and the field of pathology should co-evolve, creating a symbiotic relationship that results in high-quality reproducible, objective data.

Keywords:  digital pathology; image analysis; quantitative pathology; whole-slide imaging

Mesh:

Year:  2013        PMID: 24091812     DOI: 10.1177/0300985813503570

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


  34 in total

1.  Image analysis of immunohistochemistry is superior to visual scoring as shown for patient outcome of esophageal adenocarcinoma.

Authors:  Annette Feuchtinger; Tabitha Stiehler; Uta Jütting; Goran Marjanovic; Birgit Luber; Rupert Langer; Axel Walch
Journal:  Histochem Cell Biol       Date:  2014-08-26       Impact factor: 4.304

2.  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

3.  Ensemble of transfer learnt classifiers for recognition of cardiovascular tissues from histological images.

Authors:  Shubham Mittal
Journal:  Phys Eng Sci Med       Date:  2021-05-20

4.  Performance of residents using digital images versus glass slides on certification examination in anatomical pathology: a mixed methods pilot study.

Authors:  Lorna Mirham; Christopher Naugler; Malcolm Hayes; Nadia Ismiil; Annie Belisle; Shachar Sade; Catherine Streutker; Christina MacMillan; Golnar Rasty; Snezana Popovic; Mariamma Joseph; Manal Gabril; Penny Barnes; Richard G Hegele; Beverley Carter; George M Yousef
Journal:  CMAJ Open       Date:  2016-02-25

5.  Digital pathology in academia: Implementation and impact.

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

Review 6.  Pathology Image Analysis Using Segmentation Deep Learning Algorithms.

Authors:  Shidan Wang; Donghan M Yang; Ruichen Rong; Xiaowei Zhan; Guanghua Xiao
Journal:  Am J Pathol       Date:  2019-06-11       Impact factor: 4.307

7.  Automated erythrocyte detection and classification from whole slide images.

Authors:  Darshana Govind; Brendon Lutnick; John E Tomaszewski; Pinaki Sarder
Journal:  J Med Imaging (Bellingham)       Date:  2018-04-10

8.  Applicability of digital analysis and imaging technology in neuropathology assessment.

Authors:  William D Dunn; Marla Gearing; Yuna Park; Lifan Zhang; John Hanfelt; Jonathan D Glass; David A Gutman
Journal:  Neuropathology       Date:  2015-11-18       Impact factor: 1.906

Review 9.  Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology.

Authors:  Rohit Bhargava; Anant Madabhushi
Journal:  Annu Rev Biomed Eng       Date:  2016-07-11       Impact factor: 9.590

10.  Automated Osteosclerosis Grading of Clinical Biopsies Using Infrared Spectroscopic Imaging.

Authors:  Rupali Mankar; Carlos E Bueso-Ramos; C Cameron Yin; Juliana Elisa Hidalgo-Lopez; Sebastian Berisha; Mustafa Kansiz; David Mayerich
Journal:  Anal Chem       Date:  2019-12-13       Impact factor: 6.986

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