Purpose: The purpose of this study was to evaluate the performance of three common deformable image registration (DIR) packages across algorithms and institutions.
Methods And Materials: The Deformable Image Registration Evaluation Project (DIREP) provides ten virtual phantoms derived from computed tomography (CT) datasets of head-and-neck cancer patients over a single treatment course. Using the DIREP phantoms, DIR results from 35 institutions were submitted using either Velocity, MIM, or Eclipse. Submitted deformation vector fields (DVFs) were compared to ground-truth DVFs to calculate target registration error (TRE) for six regions of interest (ROIs). Statistical analysis was performed to determine the variability between each DIR software package and the variability of users within each algorithm.
Results: Overall mean TRE was 2.04 ± 0.35 mm for Velocity, 1.10 ± 0.29 mm for MIM, and 2.35 ± 0.15 mm for Eclipse. The MIM mean TRE was significantly different than both Velocity and Eclipse for all ROIs. Velocity and Eclipse mean TREs were not significantly different except for when evaluating the registration of the cord or mandible. Significant differences between institutions were found for the MIM and Velocity platforms. However, these differences could be explained by variations in Velocity DIR parameters and MIM software versions.
Conclusions: Average TRE was shown to be <3 mm for all three software platforms. However, maximum errors could be larger than 2 cm indicating that care should be exercised when using DIR. While MIM performed statistically better than the other packages, all evaluated algorithms had an average TRE better than the largest voxel dimension. For the phantoms studied here, significant differences between algorithm users were minimal suggesting that the algorithm used may have more impact on DIR accuracy than the particular registration technique employed. A significant difference in TRE was discovered between MIM versions showing that DIR QA should be performed after software upgrades as recommended by TG-132.
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http://dx.doi.org/10.1002/acm2.13242 | DOI Listing |
J Imaging Inform Med
January 2025
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.
View Article and Find Full Text PDFBMJ Case Rep
January 2025
Radiodiagnosis Department, Dr Ram Manohar Lohia Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Postseizure brain changes on imaging are well-known facts. Many times, oedematous brain changes can mimic ischaemic stroke. Crossed cerebellar diaschisis refers to a depression in metabolism, affecting the cerebellar hemisphere due to contralateral supratentorial abnormalities.
View Article and Find Full Text PDFComput Biol Med
January 2025
SCOPIA Research Group, University of the Balearic Islands, Dpt. of Mathematics and Computer Science, Crta. Valldemossa, Km 7.5, Palma, E-07122, Spain; Health Research Institute of the Balearic Islands (IdISBa), Palma, E-07122, Spain; Laboratory for Artificial Intelligence Applications at UIB (LAIA@UIB), Palma, E-07122, Spain; Artificial Intelligence Research Institute of the Balearic Islands (IAIB), Palma, E-07122, Spain. Electronic address:
Sickle cell disease causes erythrocytes to become sickle-shaped, affecting their movement in the bloodstream and reducing oxygen delivery. It has a high global prevalence and places a significant burden on healthcare systems, especially in resource-limited regions. Automated classification of sickle cells in blood images is crucial, allowing the specialist to reduce the effort required and avoid errors when quantifying the deformed cells and assessing the severity of a crisis.
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January 2025
Cedars-Sinai Medical Centre, Los Angeles, USA.
Objective: Accurate rotational reduction following tibial shaft fracture fixation is absent in up to 36% of cases yet may be critical for lower extremity biomechanics. The objective of this cadaveric study was to compare the results of freehand methods of reduction with software-assisted reduction.
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Biomed Phys Eng Express
January 2025
Shandong University, No. 72, Binhai Road, Jimo, Qingdao City, Shandong Province, Qingdao, 266200, CHINA.
U-Net is widely used in medical image segmentation due to its simple and flexible architecture design. To address the challenges of scale and complexity in medical tasks, several variants of U-Net have been proposed. In particular, methods based on Vision Transformer (ViT), represented by Swin UNETR, have gained widespread attention in recent years.
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