ArticlePloS one2016
Possibility Study of Scale Invariant Feature Transform (SIFT) Algorithm Application to Spine Magnetic Resonance Imaging.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Intelligent Analysis of Medical Images Based on Improved U-Net and SIFT Algorithms for Pre-Hospital Emergency Care.Diagnostics (Basel, Switzerland) · 2026Article
- A bi-channel aided stitching of atomic force microscopy images.Scientific reports · 2025Article
- Stitching brain and spinal cord DTI using cross-correlation registration: toward an atlas of spinal tracts.European radiology experimental · 2025Article
- Radiographic chest wall abnormalities in primary spontaneous pneumothorax identified by artificial intelligence.Heliyon · 2024Article
- Radiological images and machine learning: Trends, perspectives, and prospects.Computers in biology and medicine · 2019Review
- A novel image registration approach via combining local features and geometric invariants.PloS one · 2018Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study is an application of scale invariant feature transform (SIFT) algorithm to stitch the cervical-thoracic-lumbar (C-T-L) spine magnetic resonance (MR) images to provide a view of the entire spine in a single image. All MR images were acquired with fast spin echo (FSE) pulse sequence using two MR scanners (1.5 T and 3.0 T). The stitching procedures for each part of spine MR image were performed and implemented on a graphic user interface (GUI) configuration. Moreover, the stitching process is performed in two categories; manual point-to-point (mPTP) selection that performed by user specified corresponding matching points, and automated point-to-point (aPTP) selection that performed by SIFT algorithm. The stitched images using SIFT algorithm showed fine registered results and quantitatively acquired values also indicated little errors compared with commercially mounted stitching algorithm in MRI systems. Our study presented a preliminary validation of the SIFT algorithm application to MRI spine images, and the results indicated that the proposed approach can be performed well for the improvement of diagnosis. We believe that our approach can be helpful for the clinical application and extension of other medical imaging modalities for image stitching.
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