Publications by authors named "M M Obmann"
Objectives: This study evaluates the advantages in diagnostic accuracy, confidence, and reading time of additional dual-energy CT-derived reconstructions for assessing acute bowel ischemia.
Methods And Materials: This retrospective study includes 25 patients with surgically proven acute bowel ischemia and 25 gender- and age-matched controls who underwent biphasic abdominal dual-energy CT. Two fellowship-trained abdominal radiologists and two residents evaluated all cases with and without additional dual-energy CT-derived iodine maps and virtual non-contrast images.
The purpose of this study is to assess segmentation reproducibility of artificial intelligence-based algorithm, TotalSegmentator, across 34 anatomical structures using multiphasic abdominal CT scans comparing unenhanced, arterial, and portal venous phases in the same patients. A total of 1252 multiphasic abdominal CT scans acquired at our institution between January 1, 2012, and December 31, 2022, were retrospectively included. TotalSegmentator was used to derive volumetric measurements of 34 abdominal organs and structures from the total of 3756 CT series.
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- - The study aimed to compare the quality and effectiveness of deep learning reconstructed (DLR) 0.55 T MRI against the conventional 3 T MRI for identifying and grading knee injuries in trauma patients.
- - Conducted on 26 patients, the study involved paired MRI scans, where four radiologists assessed the images based on quality, structural anomalies, and their confidence in reporting findings.
- - Results indicated that DLR 0.55 T MRI achieved good image quality and nearly perfect agreement with 3 T MRI in identifying anomalies, proving it as a reliable alternative with high confidence levels from radiologists.
Objectives: To evaluate an optimized deep leaning-based image post-processing technique in lumbar spine MRI at 0.55 T in terms of image quality and image acquisition time.
Materials And Methods: Lumbar spine imaging was conducted on 18 patients using a 0.