Comparison of lumbar disc degeneration grading between deep learning model SpineNet and radiologist: a longitudinal study with a 14-year follow-up

Niko Murto; Teija Lund; Hannu Kautiainen; Katariina Luoma; Liisa Kerttula

doi:10.1007/s00586-025-08900-2

Comparison of lumbar disc degeneration grading between deep learning model SpineNet and radiologist: a longitudinal study with a 14-year follow-up

Niko Murto, Teija Lund, Hannu Kautiainen, Katariina Luoma, Liisa Kerttula

Research output: Contribution to journal › Article › Scientific › peer-review

Abstract

To assess the agreement between lumbar disc degeneration (DD) grading by the convolutional neural network model SpineNet and radiologist’s visual grading.

Original language	English
Journal	European Spine Journal
Number of pages	7
ISSN	0940-6719
DOIs	https://doi.org/10.1007/s00586-025-08900-2
Publication status	Published - 15 May 2025
MoE publication type	A1 Journal article-refereed

Fields of Science

Artificial intelligence
Disc degeneration
Machine learning
Pfirrmann
Validation
113 Computer and information sciences
217 Medical engineering

Access to Document

10.1007/s00586-025-08900-2

s00586-025-08900-2Final published version, 1.1 MBLicence: CC BY

Cite this

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title = "Comparison of lumbar disc degeneration grading between deep learning model SpineNet and radiologist: a longitudinal study with a 14-year follow-up",

abstract = "To assess the agreement between lumbar disc degeneration (DD) grading by the convolutional neural network model SpineNet and radiologist{\textquoteright}s visual grading.",

keywords = "Artificial intelligence, Disc degeneration, Machine learning, Pfirrmann, Validation, 113 Computer and information sciences, 217 Medical engineering",

author = "Niko Murto and Teija Lund and Hannu Kautiainen and Katariina Luoma and Liisa Kerttula",

year = "2025",

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language = "English",

journal = "European Spine Journal",

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T1 - Comparison of lumbar disc degeneration grading between deep learning model SpineNet and radiologist: a longitudinal study with a 14-year follow-up

AU - Murto, Niko

AU - Lund, Teija

AU - Kautiainen, Hannu

AU - Luoma, Katariina

AU - Kerttula, Liisa

PY - 2025/5/15

Y1 - 2025/5/15

N2 - To assess the agreement between lumbar disc degeneration (DD) grading by the convolutional neural network model SpineNet and radiologist’s visual grading.

AB - To assess the agreement between lumbar disc degeneration (DD) grading by the convolutional neural network model SpineNet and radiologist’s visual grading.

KW - Artificial intelligence

KW - Disc degeneration

KW - Machine learning

KW - Pfirrmann

KW - Validation

KW - 113 Computer and information sciences

KW - 217 Medical engineering

U2 - 10.1007/s00586-025-08900-2

DO - 10.1007/s00586-025-08900-2

M3 - Article

SN - 0940-6719

JO - European Spine Journal

JF - European Spine Journal

ER -