ArticlePloS one2014
Detection of time-varying structures by large deformation diffeomorphic metric mapping to aid reading of high-resolution CT images of the lung.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review on the Use of Registration-Based Change Tracking Methods in Longitudinal Radiological Images.Journal of imaging informatics in medicine · 2025Pooled it
- The Efficacy of CT Temporal Subtraction Images for Fibrodysplasia Ossificans Progressiva.Tomography (Ann Arbor, Mich.) · 2023Article
- CT-derived 3D-diaphragm motion in emphysema and IPF compared to normal subjects.Scientific reports · 2021Article
- CT temporal subtraction: techniques and clinical applications.Quantitative imaging in medicine and surgery · 2021Article
- Adaptive Voxel Matching for Temporal CT Subtraction.Journal of digital imaging · 2020Article
- Quantifying local tumor morphological changes with Jacobian map for prediction of pathologic tumor response to chemo-radiotherapy in locally advanced esophageal cancer.Physics in medicine and biology · 2018Article
- Line-Enhanced Deformable Registration of Pulmonary Computed Tomography Images Before and After Radiation Therapy With Radiation-Induced Fibrosis.Technology in cancer research & treatment · 2018Article
- Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases.Radiology · 2017Article
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Authors and funding
5 authors.
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Abstract
objectivesTo evaluate the accuracy of advanced non-linear registration of serial lung Computed Tomography (CT) images using Large Deformation Diffeomorphic Metric Mapping (LDDMM).
methodsFIFTEEN CASES OF LUNG CANCER WITH SERIAL LUNG CT IMAGES (INTERVAL: 62.2±26.9 days) were used. After affine transformation, three dimensional, non-linear volume registration was conducted using LDDMM with or without cascading elasticity control. Registration accuracy was evaluated by measuring the displacement of landmarks placed on vessel bifurcations for each lung segment. Subtraction images and Jacobian color maps, calculated from the transformation matrix derived from image warping, were generated, which were used to evaluate time-course changes of the tumors.
resultsThe average displacement of landmarks was 0.02±0.16 mm and 0.12±0.60 mm for proximal and distal landmarks after LDDMM transformation with cascading elasticity control, which was significantly smaller than 3.11±2.47 mm and 3.99±3.05 mm, respectively, after affine transformation. Emerged or vanished nodules were visualized on subtraction images, and enlarging or shrinking nodules were displayed on Jacobian maps enabled by highly accurate registration of the nodules using LDDMM. However, some residual misalignments were observed, even with non-linear transformation when substantial changes existed between the image pairs.
conclusionsLDDMM provides accurate registration of serial lung CT images, and temporal subtraction images with Jacobian maps help radiologists to find changes in pulmonary nodules.
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