• Neuroimaging Clin. N. Am. · Nov 2020

    Review Comparative Study

    Knowledge Based Versus Data Based: A Historical Perspective on a Continuum of Methodologies for Medical Image Analysis.

    • Peter Savadjiev, Caroline Reinhold, Diego Martin, and Reza Forghani.
    • Department of Diagnostic Radiology, McGill University, Room B02 9389, 1001 Decarie Boulevard, Montreal, Quebec H4A 3J1, Canada; School of Computer Science, McGill University, Montreal, Quebec, Canada; Medical Physics Unit, Department of Oncology, McGill University, Montreal, Quebec, Canada; Augmented Intelligence & Precision Health Laboratory (AIPHL), Department of Diagnostic Radiology, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada. Electronic address: peter.savadjiev@mcgill.ca.
    • Neuroimaging Clin. N. Am. 2020 Nov 1; 30 (4): 401-415.

    AbstractThe advent of big data and deep learning algorithms has promoted a major shift toward data-driven methods in medical image analysis recently. However, the medical image analysis field has a long and rich history inclusive of both knowledge-driven and data-driven methodologies. In the present article, we provide a historical review of an illustrative sample of medical image analysis methods and locate them along a knowledge-driven versus data-driven continuum. In doing so, we highlight the historical importance as well as current-day relevance of more traditional, knowledge-based artificial intelligence approaches and their complementarity with fully data-driven techniques such as deep learning.Copyright © 2020 Elsevier Inc. All rights reserved.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…