Background: Artificial intelligence (AI) is known to provide effective means to accelerate and facilitate clinical and research processes. So in this study it was aimed to compare a AI-based method for cardiac segmentation in positron emission tomography/computed tomography (PET/CT) scans with manual segmentation to assess global cardiac atherosclerosis burden.
Methods: A trained convolutional neural network (CNN) was used for cardiac segmentation in F-sodium fluoride PET/CT scans of 29 healthy volunteers and 20 angina pectoris patients and compared with manual segmentation. Parameters for segmented volume (Vol) and mean, maximal, and total standardized uptake values (SUVmean, SUVmax, SUVtotal) were analyzed by Bland-Altman Limits of Agreement. Repeatability with AI-based assessment of the same scans is 100%. Repeatability (same conditions, same operator) and reproducibility (same conditions, two different operators) of manual segmentation was examined by re-segmentation in 25 randomly selected scans.
Results: Mean (± SD) values with manual vs. CNN-based segmentation were Vol 617.65 ± 154.99 mL vs 625.26 ± 153.55 mL (P = .21), SUVmean 0.69 ± 0.15 vs 0.69 ± 0.15 (P = .26), SUVmax 2.68 ± 0.86 vs 2.77 ± 1.05 (P = .34), and SUVtotal 425.51 ± 138.93 vs 427.91 ± 132.68 (P = .62). Limits of agreement were - 89.42 to 74.2, - 0.02 to 0.02, - 1.52 to 1.32, and - 68.02 to 63.21, respectively. Manual segmentation lasted typically 30 minutes vs about one minute with the CNN-based approach. The maximal deviation at manual re-segmentation was for the four parameters 0% to 0.5% with the same and 0% to 1% with different operators.
Conclusion: The CNN-based method was faster and provided values for Vol, SUVmean, SUVmax, and SUVtotal comparable to the manually obtained ones. This AI-based segmentation approach appears to offer a more reproducible and much faster substitute for slow and cumbersome manual segmentation of the heart.
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http://dx.doi.org/10.1007/s12350-021-02758-9 | DOI Listing |
Sensors (Basel)
January 2025
Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Yongin-si 16890, Republic of Korea.
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School of Biomedical Engineering, Tsinghua University, Shuang Qing Road, Beijing 100084, China.
Mastoidectomy is critical in acoustic neuroma surgery, where precise planning of the bone milling area is essential for surgical navigation. The complexity of representing the irregular volumetric area and the presence of high-risk structures (e.g.
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January 2025
Space Robotics Research Group (SpaceR), Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, L-1855 Luxembourg, Luxembourg.
Malaria remains a global health concern, with 249 million cases and 608,000 deaths being reported by the WHO in 2022. Traditional diagnostic methods often struggle with inconsistent stain quality, lighting variations, and limited resources in endemic regions, making manual detection time-intensive and error-prone. This study introduces an automated system for analyzing Romanowsky-stained thick blood smears, focusing on image quality evaluation, leukocyte detection, and malaria parasite classification.
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Ophthalmology Section, Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.
To report the cosmetic, clinical, and visual outcomes of a combined surgical approach for treating a corneal/limbal dermoid using excision and a three-layered amniotic membrane graft with fibrin glue. An 18-year-old female presented with impaired vision and ocular discomfort caused by a prominent dome-shaped limbal congenital dermoid on the inferotemporal cornea, resulting in a significant aesthetic concern. A full assessment, including refraction, best-corrected visual acuity (BCVA), corneal topography, aberrometry and anterior segment OCT (AS-OCT) was conducted to plan the surgical approach.
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Department of Radiology, Weill Cornell Medicine, New York, NY 10022, USA.
: Accurate and reproducible spleen volume measurements are essential for assessing treatment response and disease progression in myelofibrosis. This study evaluates techniques for measuring spleen volume on abdominal MRI. : In 20 patients with bone marrow biopsy-proven myelofibrosis, 5 observers independently measured spleen volume on 3 abdominal MRI pulse sequences, 3D-spoiled gradient echo T1, axial single-shot fast spin echo (SSFSE) T2, and coronal SSFSE T2, using ellipsoidal approximation, manual contouring, and 3D nnU-Net model-assisted contouring comparing coefficients of variation.
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