CoLumbo is a software for analysis of lumbar spine images obtained with MRI. The purpose of CoLumbo is to assist with the reading of MRI images on the lumbar spine and to provide information on detected pathologies and abnormalities, and reduce the time to record the readings. CoLumbo uses a machine learning algorithms based on fully convolutional neural networks combined with medical domain knowledge.
Product specifications Information source: Vendor
Last updated: June 28, 2022
Product name CoLumbo
Company Smart Soft Healthcare
Subspeciality Spine
Modality MR
Disease targeted Herniation, bulging, hypo/hyperlordosis, central spinal stenosis, nerve root impingement, reduced vertebral body and disc height, listhesis
Key-features Lumbar spine annotation, smart navigation, editable report, editable separate pathology report, measurement calculation based on segmentation
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion
Data characteristics
Population MRI lumbar spine studies, age – 18 to 70 (included)
Input Lumbar spine MR, Magnetic Field Strength 1,5-3T. At least one sagittal T2w sequence containing 5 slices or more. Scanning Sequence – SE
Input format DICOM
Output Segmentation overlay, probability score per pathology, draft radiology report, image annotations, table of quantified values, list with measurements.
Output format DICOM, DICOM PDF
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone third party application
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 10 - 60 seconds
Certified, Class IIa , MDD
510(k) cleared, Class II
Market presence
On market since 03-2021
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Pay-per-use, Subscription
Based on Number of analyses
Peer reviewed papers on performance

  • Detection of Degenerative Changes on MR Images of the Lumbar Spine with a Convolutional Neural Network: A Feasibility Study (read)

Non-peer reviewed papers on performance
Other relevant papers