Benchmarking of algorithms for 3D tissue reconstruction

Kimmo Kartasalo, Leena Latonen, Tapio Visakorpi, Matti Nykter, Pekka Ruusuvuori

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    2 Citations (Scopus)

    Abstract

    Studying tissue structure in 3D is beneficial in many applications. Reconstructing the structure based on histological sections has the advantages of high resolution and compatibility with conventional staining and interpretation techniques. However, obtaining an accurate 3D reconstruction based on a sequence of 2D sections is a difficult task. Evaluating the accuracy of such reconstructions is also challenging and it is often performed based only on visual inspections or a single indirect numerical measure. Here, we present a benchmarking framework composed of a panel of complementary metrics for assessing the quality of 3D reconstructions. We then apply the framework to evaluate the performance of several popular image registration algorithms in this context.
    Original languageEnglish
    Title of host publication2016 IEEE International Conference on Image Processing (ICIP)
    PublisherIEEE
    Pages2360-2364
    Number of pages5
    ISBN (Electronic)978-1-4673-9961-6
    DOIs
    Publication statusPublished - 2016
    Publication typeA4 Article in conference proceedings
    EventIEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING -
    Duration: 1 Jan 2016 → …

    Conference

    ConferenceIEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING
    Period1/01/16 → …

    Keywords

    • 3D reconstruction
    • Benchmark testing
    • Image reconstruction
    • Image registration
    • Indexes
    • Measurement
    • Standards
    • Three-dimensional displays
    • benchmark
    • digital pathology
    • histology

    Publication forum classification

    • Publication forum level 1

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