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Biomedical image processing in pathology: a review

H Nazeran1, F Rice, W Moran

  • 1School of Engineering, Flinders University of South Australia.

Australasian Physical & Engineering Sciences in Medicine
|March 1, 1995
PubMed
Summary
This summary is machine-generated.

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Computer-aided image processing enhances quantitative pathology by analyzing cellular attributes. This review covers image analysis techniques, cytometric/histometric methods, and advanced applications like 3D imaging and neural networks.

Area of Science:

  • Digital pathology
  • Computational imaging
  • Medical image analysis

Background:

  • Pathologists rely on visual assessment of specimen attributes (size, shape, color) for diagnosis.
  • Quantitative pathology utilizes computer-aided image processing and analysis systems.
  • Significant advancements in computational image processing have occurred since 1987.

Purpose of the Study:

  • To summarize basic image processing and analysis techniques in pathology and cytology.
  • To review computational image processing applications in quantitative pathology.
  • To provide an overview of advanced techniques including 3D imaging and artificial neural networks.

Main Methods:

  • Introduction to image enhancement, segmentation, morphometry, and visualization.

Related Experiment Videos

  • Review of image cytometric and histometric methods, standards, and applications.
  • Discussion of 3D confocal image processing, artificial neural networks, and database management.

    • Main Results:

    • Basic image processing techniques serve as preprocessing steps for microscopic image analysis.
    • Established methods for image cytometry and histometry are reviewed.
    • Emerging applications in 3D imaging and artificial intelligence are highlighted.

    Conclusions:

    • Computational image analysis is crucial for quantitative pathology.
    • A range of techniques, from basic to advanced, are available for pathological image analysis.
    • Future directions include integrated microscope-computer systems and advanced data management.