Martin Segeroth
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View article: Liver Segment and Lesion Segmentation on CT and MRI: An Open-Source Contribution to TotalSegmentator
Liver Segment and Lesion Segmentation on CT and MRI: An Open-Source Contribution to TotalSegmentator Open
This study aims to develop a tool based on deep learning algorithms for automatic liver segment and liver lesion segmentation on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). We demonstrate its clinical utility using a qua…
View article: Redefining MRI-Based Skull Segmentation Through AI-Driven Multimodal Integration
Redefining MRI-Based Skull Segmentation Through AI-Driven Multimodal Integration Open
Skull segmentation in magnetic resonance imaging (MRI) is essential for cranio-maxillofacial (CMF) surgery planning, yet manual approaches are time-consuming and error-prone. Computed tomography (CT) provides superior bone contrast but exp…
View article: Correction: Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI
Correction: Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI Open
View article: Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI
Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI Open
The aim of this study was to develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysms (UICA) in 3D TOF-MRI and compare models trained on datasets with aneurysm-like differen…
View article: Automatic Segmentation of Cardiovascular Structures on Chest CT Data Sets: An Update of the TotalSegmentator
Automatic Segmentation of Cardiovascular Structures on Chest CT Data Sets: An Update of the TotalSegmentator Open
Accurate segmentations and enhanced segmentations of previously included CV structures were successfully implemented. This suggests further usage in research studies while still running on conventional computers with or without a dedicated…
View article: Intra-Individual Reproducibility of Automated Abdominal Organ Segmentation—Performance of TotalSegmentator Compared to Human Readers and an Independent nnU-Net Model
Intra-Individual Reproducibility of Automated Abdominal Organ Segmentation—Performance of TotalSegmentator Compared to Human Readers and an Independent nnU-Net Model Open
View article: Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI
Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI Open
Purpose: To develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysms (UICA) in 3D TOF-MRI, and compare models trained on datasets with aneurysm-like differential diagnoses. …
View article: Cardiac Cine MRI Using a Commercially Available 0.55-T Scanner
Cardiac Cine MRI Using a Commercially Available 0.55-T Scanner Open
Purpose To compare parameters of left ventricular (LV) and right ventricular (RV) volume and function between a commercially available 0.55-T low-field-strength cardiac cine MRI scanner and a 1.5-T scanner. Materials and Methods In this pr…
View article: TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI
TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI Open
Since the introduction of TotalSegmentator CT, there is demand for a similar robust automated MRI segmentation tool that can be applied across all MRI sequences and anatomic structures. In this retrospective study, a nnU-Net model (TotalSe…
View article: CMR LGE for Assessment of Accuracy of the ECG Criteria of the Fourth Universal Definition of Myocardial Infarction
CMR LGE for Assessment of Accuracy of the ECG Criteria of the Fourth Universal Definition of Myocardial Infarction Open
View article: Noninvasive Assessment of Cardiopulmonary Hemodynamics Using Cardiovascular Magnetic Resonance Pulmonary Transit Time
Noninvasive Assessment of Cardiopulmonary Hemodynamics Using Cardiovascular Magnetic Resonance Pulmonary Transit Time Open
Introduction: Pulmonary transit time (PTT) is the time it takes blood to pass from the right ventricle to the left ventricle via the pulmonary circulation, making it a potentially useful marker for heart failure. We assessed the associatio…
View article: Radiology weather forecast: A retrospective analysis of predictability of median daily polytrauma-CT occurrence based on weather data
Radiology weather forecast: A retrospective analysis of predictability of median daily polytrauma-CT occurrence based on weather data Open
Prediction of polytrauma-CT examination volumes may be used to improve resource planning.
View article: Impact of retraining a deep learning algorithm for improving guideline-compliant aortic diameter measurements on non-gated chest CT
Impact of retraining a deep learning algorithm for improving guideline-compliant aortic diameter measurements on non-gated chest CT Open
Re-training of the DL tool improved diameter assessment, resulting in a total of 95.5% correct measurements. Our data suggests that the re-trained DL tool can be applied even in non-ECG-gated chest CT including both, CE and non-CE exams.
View article: Pulmonary transit time of cardiovascular magnetic resonance perfusion scans for quantification of cardiopulmonary haemodynamics
Pulmonary transit time of cardiovascular magnetic resonance perfusion scans for quantification of cardiopulmonary haemodynamics Open
Aims Pulmonary transit time (PTT) is the time blood takes to pass from the right ventricle to the left ventricle via pulmonary circulation. We aimed to quantify PTT in routine cardiovascular magnetic resonance imaging perfusion sequences. …
View article: TotalSegmentator: robust segmentation of 104 anatomical structures in CT images
TotalSegmentator: robust segmentation of 104 anatomical structures in CT images Open
We present a deep learning segmentation model that can automatically and robustly segment all major anatomical structures in body CT images. In this retrospective study, 1204 CT examinations (from the years 2012, 2016, and 2020) were used …
View article: Automated Detection, Segmentation, and Classification of Pericardial Effusions on Chest CT Using a Deep Convolutional Neural Network
Automated Detection, Segmentation, and Classification of Pericardial Effusions on Chest CT Using a Deep Convolutional Neural Network Open
Pericardial effusions (PEFs) are often missed on Computed Tomography (CT), which particularly affects the outcome of patients presenting with hemodynamic compromise. An automatic PEF detection, segmentation, and classification tool would e…