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Michael Dieckmeyer

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Articles 62
Citations 807
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Recent Articles
1.
Sollmann N, Dieckmeyer M, Carballido-Gamio J, Van A, Karampinos D, Feuerriegel G, et al.
Semin Musculoskelet Radiol . 2024 Oct; 28(5):576-593. PMID: 39406221
Metabolic bone diseases (MBDs) are a diverse group of diseases, affecting the mass or structure of bones and leading to reduced bone quality. Parameters representing different aspects of bone health...
2.
Liu L, Pua R, Dieckmeyer M, Shapira N, Sahbaee P, Gang G, et al.
J Med Imaging (Bellingham) . 2024 Jul; 11(Suppl 1):S12806. PMID: 39072220
Purpose: Evaluation of iodine quantification accuracy with varying iterative reconstruction level, patient habitus, and acquisition mode on a first-generation dual-source photon-counting computed tomography (PCCT) system. Approach: A multi-energy CT phantom...
3.
Bodden J, Dieckmeyer M, Sollmann N, Ruhling S, Prucker P, Loffler M, et al.
Quant Imaging Med Surg . 2023 Sep; 13(9):5472-5482. PMID: 37711780
Background: To investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in...
4.
Bodden J, Dieckmeyer M, Sollmann N, Burian E, Ruhling S, Loffler M, et al.
Front Endocrinol (Lausanne) . 2023 Aug; 14:1207949. PMID: 37529605
Objectives: To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models....
5.
Schlaeger S, Shit S, Eichinger P, Hamann M, Opfer R, Kruger J, et al.
Insights Imaging . 2023 Jul; 14(1):123. PMID: 37454342
Background: Contrast-enhancing (CE) lesions are an important finding on brain magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) but can be missed easily. Automated solutions for reliable CE...
6.
Goller S, Foreman S, Rischewski J, Weissinger J, Dietrich A, Schinz D, et al.
Eur Spine J . 2023 Jul; 32(12):4314-4320. PMID: 37401945
Purpose: To assess the diagnostic performance of three-dimensional (3D) CT-based texture features (TFs) using a convolutional neural network (CNN)-based framework to differentiate benign (osteoporotic) and malignant vertebral fractures (VFs). Methods:...
7.
Dieckmeyer M, Sollmann N, Kupfer K, Loffler M, Paprottka K, Kirschke J, et al.
Clin Neuroradiol . 2023 Mar; 33(3):591-610. PMID: 36862232
In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments,...
8.
Dieckmeyer M, Sollmann N, Kupfer K, Loffler M, Paprottka K, Kirschke J, et al.
Clin Neuroradiol . 2022 Nov; 33(2):271-291. PMID: 36416936
The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional spine imaging. In the last decades, the technological advancement, increasing availability and clinical success of...
9.
Leonhardt Y, Dieckmeyer M, Zoffl F, Feuerriegel G, Sollmann N, Junker D, et al.
Biomedicines . 2022 Sep; 10(9). PMID: 36140176
Chemical shift encoding-based water−fat MRI (CSE-MRI)-derived proton density fat fraction (PDFF) has been used for non-invasive assessment of regional body fat distributions. More recently, texture analysis (TA) has been proposed...
10.
Greve T, Rayudu N, Dieckmeyer M, Boehm C, Ruschke S, Burian E, et al.
Front Endocrinol (Lausanne) . 2022 Jul; 13:900356. PMID: 35898459
Purpose: Osteoporosis is prevalent and entails alterations of vertebral bone and marrow. Yet, the spine is also a common site of metastatic spread. Parameters that can be non-invasively measured and...