Atlas-Based Segmentation of Degenerated Lumbar Intervertebral Discs From MR Images of the Spine

Abstract

Intervertebral disc degeneration is an age-associated condition related to chronic back pain, while its consequences are responsible for over 90 % of spine surgical procedures. In clinical practice, MRI is the modality of reference for diagnosing disc degeneration. In this study, we worked toward 2-D semiautomatic segmentation of both normal and degenerated lumbar intervertebral discs from T2-weighted midsagittal MR images of the spine. This task is challenged by partial volume effects and overlapping gray-level values between neighboring tissue classes. To overcome these problems three variations of atlas-based segmentation using a probabilistic atlas of the intervertebral disc were developed and their accuracies were quantitatively evaluated against manually segmented data. The best overall performance, when considering the tradeoff between segmentation accuracy and time efficiency, was accomplished by the atlas-robust-fuzzy c-means approach, which combines prior anatomical knowledge by means of a rigidly registered probabilistic disc atlas with fuzzy clustering techniques incorporating smoothness constraints. The dice similarity indexes of this method were 91.6 % for normal and 87.2 % for degenerated discs. Research in progress utilizes the proposed approach as part of a computer-aided diagnosis system for quantification and characterization of disc degeneration severity. Moreover, this approach could be exploited in computer-assisted spine surgery.

Lumbar Spine Disc Herniation Diagnosis with a Joint Shape Model

“…Moreover, our shape-based classifier outperforms the recent work of Michopoulou et al [11] which is based on an intensity-based classifier. Both recent works test on 33 and 34 cases with an average herniation detection accuracy of 91% and 88%, respectively.…”

“…They patented their work as a visualization tool for educational purposes. Recently, Michopoulou et al [11] applied three variations of fuzzy c-means (FCM) to perform atlas-based disc segmentation. Then, they used this segmentation for classification of the disc as either a normal or degenerative disc.…”

A Novel Method VESTAL to Label Lumber Vertebrae and Intervertebral Discs

“…In manual labelling, radiologist labels the vertebrae by identifying one reference point generally and this reference point is sacrum or atlas. Accurate labelling of the vertebrae and IVDs are necessary because the backbone has wide variability including degree of bending of the vertebral column, sizes, shapes and appearances of discs and vertebrae [2][3]. Figure 1 shows a normal and abnormal Lumber spine images.…”

Vertebral Body Segmentation in MRI via Convex Relaxation and Distribution Matching

“…Precise segmentation of the vertebral bodies (VBs) and intervertebral discs (IVDs) in MRI is an essential step towards thorough, reproducible and fast diagnosis of spine deformities [7,11]. Unlike CT, MRI scans depict soft-tissue structures, thereby allowing to characterize/quantify common spine disorders such as herniation [6] and disc degeneration [11].…”

“…Unlike CT, MRI scans depict soft-tissue structures, thereby allowing to characterize/quantify common spine disorders such as herniation [6] and disc degeneration [11]. However, most of related spinesegmentation works focused on CT, mainly because the latter affords high contrast for bony structures, e.g., [8,10,16], among others.…”