Literature DB >> 33063645

DICOM Format and Protocol Standardization-A Core Requirement for Digital Pathology Success.

David A Clunie1.   

Abstract

As the use of digital techniques in toxicologic pathology expands, challenges of scalability and interoperability come to the fore. Proprietary formats and closed single-vendor platforms prevail but depend on the availability and maintenance of multiformat conversion libraries. Expedient for small deployments, this is not sustainable at an industrial scale. Primarily known as a standard for radiology, the Digital Imaging and Communications in Medicine (DICOM) standard has been evolving to support other specialties since its inception, to become the single ubiquitous standard throughout medical imaging. The adoption of DICOM for whole slide imaging (WSI) has been sluggish. Prospects for widespread commercially viable clinical use of digital pathology change the incentives. Connectathons using DICOM have demonstrated its feasibility for WSI and virtual microscopy. Adoption of DICOM for digital and computational pathology will allow the reuse of enterprise-wide infrastructure for storage, security, and business continuity. The DICOM embedded metadata allows detached files to remain useful. Bright-field and multichannel fluorescence, Z-stacks, cytology, and sparse and fully tiled encoding are supported. External terminologies and standard compression schemes are supported. Color consistency is defined using International Color Consortium profiles. The DICOM files can be dual personality Tagged Image File Format (TIFF) for legacy support. Annotations for computational pathology results can be encoded.

Keywords:  DICOM; TIFF; enterprise imaging; image metadata; interoperability; virtual microscopy; whole slide imaging

Year:  2020        PMID: 33063645     DOI: 10.1177/0192623320965893

Source DB:  PubMed          Journal:  Toxicol Pathol        ISSN: 0192-6233            Impact factor:   1.902


  3 in total

1.  Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks.

Authors:  Haridimos Kondylakis; Esther Ciarrocchi; Leonor Cerda-Alberich; Ioanna Chouvarda; Lauren A Fromont; Jose Manuel Garcia-Aznar; Varvara Kalokyri; Alexandra Kosvyra; Dawn Walker; Guang Yang; Emanuele Neri
Journal:  Eur Radiol Exp       Date:  2022-07-01

Review 2.  Deep Learning Approaches and Applications in Toxicologic Histopathology: Current Status and Future Perspectives.

Authors:  Shima Mehrvar; Lauren E Himmel; Pradeep Babburi; Andrew L Goldberg; Magali Guffroy; Kyathanahalli Janardhan; Amanda L Krempley; Bhupinder Bawa
Journal:  J Pathol Inform       Date:  2021-11-01

Review 3.  Software tools and platforms in Digital Pathology: a review for clinicians and computer scientists.

Authors:  Rodrigo Escobar Díaz Guerrero; Lina Carvalho; Thomas Bocklitz; Juergen Popp; José Luis Oliveira
Journal:  J Pathol Inform       Date:  2022-06-03
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.