Composite Dataset of Lumbar Spine Mid-Sagittal Images with Annotations and Clinically Relevant Spinal Measurements

Published: 2 March 2021| Version 2 | DOI: 10.17632/k3b363f3vz.2
Muhammad Usman Akram,
Imtiaz Ahmad Taj,
Muhammad Asad Qureshi,
Muhammad Babar Khan


This composite dataset comprising of mid-sagittal views of lumbar spine is composed of images of lumbar spine with ground truth images duly labelled/annotated as well the spinal measurements. The purpose of creating this dataset was to establish a strong correlation in the images with the spinal measurements being clinically relevant. Presently, these measurements are being taken either completely through manual methods or by the use of computer assisted tools. The spinal measurements are clinically significant for a spinal surgeon before suggesting or shortlisting suitable surgical intervention procedure. Traditionally, the spinal surgeon evaluates the condition of the patient before surgical procedure in order to ascertain the usefulness of the adopted procedure. It also helps the surgeon in establishing a relation regarding effectiveness of the procedure adopted. For example, in case of spinal fusion procedure, will the fusion procedure be able to restore the spinal balance is a question for which the answered is obtained through making relevant spinal measurements, including lumbar lordotic curve angle, both segmental and for whole lumbar spine, lumbosacral angle, spinal heights, dimensions of vertebral bodies etc. The Composite Dataset is acquired in following steps:- 1. Exporting mid-sagittal view from the MRI dataset. (Originally taken from Sudirman, Sud; Al Kafri, Ala; natalia, friska; Meidia, Hira; Afriliana, Nunik; Al-Rashdan, Wasfi; Bashtawi, Mohammad; Al-Jumaily, Mohammed (2019), “Label Image Ground Truth Data for Lumbar Spine MRI Dataset”, Mendeley Data, V2, doi: 10.17632/zbf6b4pttk.2). The original dataset comprises of axial views with annotations however, to determine the efficacy of spinal deformities and analyzing spinal balance sagittal views are used instead. 2. Manual labelling of lumbar vertebral bodies from L1 to L5 and first sacrum bone. Total 6 regions were labelled in consultation with expert radiologists followed by validation by expert spinal surgeon. 3. Performing fully automatic spinal measurements, including, vertebral bodies identification and labelling, lumbar height, lumbosacral angle, lumbar lordotic angle, estimation of spinal curve, intervertebral body dimensions, vertebral body dimensions. All the angular measurements are in degrees, whereas the distance measurements are in millimeters. A total of 514 images and annotations with spinal measurements can be downloaded with request to please cite out work in your research.



Capital University of Science and Technology, National University of Science & Technology


Image Understanding, Automated Segmentation, Lordosis, Lumbar Spine, Spinal Disorder, Medical Image Processing, Deep Learning