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Computer Vision and Deep Learning in Small Animal Cytology and Slide Review.

Candice P Chu1

  • 1Department of Veterinary Pathobiology, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, TX, USA.

The Veterinary Clinics of North America. Small Animal Practice
|May 18, 2026
PubMed
Summary

Computer vision (CV), a type of artificial intelligence (AI), is increasingly used in veterinary cytology for tasks like blood smear analysis. This review covers CV basics, current research, and discusses its adoption, validation, and impact on veterinary practice.

Keywords:
AI literacyComputer visionConvolutional neural networksCytologyDeep learningHematologyMachine learningPosition statement

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Area of Science:

  • Veterinary Medicine
  • Artificial Intelligence
  • Computer Vision

Background:

  • Computer vision (CV) is an emerging artificial intelligence (AI) application with increasing relevance to veterinary cytology.
  • Current applications include small animal cytology and blood smear examination.

Purpose of the Study:

  • To provide a foundational overview of CV concepts and model architectures.
  • To summarize current research progress in veterinary cytology.
  • To discuss trends, challenges, and educational needs for CV adoption in veterinary practice.

Main Methods:

  • Review of current scientific literature on CV in veterinary cytology.
  • Analysis of trends in validation, implementation, and regulation.
  • Discussion of educational needs and professional impact.

Main Results:

  • CV shows significant potential in veterinary cytology, particularly for blood smear analysis.
  • Gaps exist in transparency and standardization of CV tools.
  • Concerns regarding deskilling and workforce impact require attention.

Conclusions:

  • Informed adoption of CV tools in veterinary practice is crucial.
  • Emphasis on validation, professional oversight, and AI literacy is necessary.
  • Addressing standardization and transparency gaps will facilitate responsible integration.