A5067504823- History of Medicine Studies
- Paleopathology and ancient diseases
- Advanced MRI Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Cardiac Imaging and Diagnostics
- Advanced X-ray and CT Imaging
- Forensic Anthropology and Bioarchaeology Studies
- MRI in cancer diagnosis
- Ancient Near East History
- Medical History and Innovations
- Medical History and Research
- Prostate Cancer Treatment and Research
- Advanced Neuroimaging Techniques and Applications
- Prostate Cancer Diagnosis and Treatment
- Medical Imaging and Analysis
- Hepatocellular Carcinoma Treatment and Prognosis
- Medical Image Segmentation Techniques
- Medical Imaging Techniques and Applications
- Liver Disease Diagnosis and Treatment
- Extracellular vesicles in disease
- Systemic Lupus Erythematosus Research
- Pancreatic and Hepatic Oncology Research
- Brain Tumor Detection and Classification
- Radiation Dose and Imaging
- Rheumatoid Arthritis Research and Therapies
Charité - Universitätsmedizin Berlin
2013-2024
Humboldt-Universität zu Berlin
2013-2024
Freie Universität Berlin
2021-2024
Mie University
2023-2024
Daiichi Sankyo (Germany)
2023
Tohoku University
2023
Deutsche Forschungsgemeinschaft
2023
Abstract Magnetic resonance imaging (MRI) provides detailed anatomical images of the prostate and its zones. It has a crucial role for many diagnostic applications. Automatic segmentation such as that zones from MR facilitates therapeutic However, lack clear boundary, tissue heterogeneity, wide interindividual variety shapes make this very challenging task. To address problem, we propose new neural network to automatically segment We term algorithm Dense U-net it is inspired by two existing...
Abstract Objectives To develop and evaluate a deep convolutional neural network (DCNN) for automated liver segmentation, volumetry, radiomic feature extraction on contrast-enhanced portal venous phase magnetic resonance imaging (MRI). Materials methods This retrospective study included hepatocellular carcinoma patients from an institutional database with MRI. After manual the data was randomly split into independent training, validation, internal testing sets. From collaborating institution,...
Abstract Objectives To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative (AIDR 3D), and model-based (FIRST). Methods Effects on features were investigated using a phantom that realistically mimicked 65-year-old patient’s abdomen hepatic metastases. The was scanned at 18 doses from 0.2 to 4 mGy, 20 repeated scans per dose. Images reconstructed FBP, AIDR 3D, FIRST, AiCE. Ninety-three extracted 24...
Multiparametric MRI has high diagnostic accuracy for detecting prostate cancer, but non-invasive prediction of tumor grade remains challenging. Characterizing perfusion by exploiting the fractal nature vascular anatomy might elucidate aggressive potential a tumor. This study introduces concept analysis characterizing cancer and reports about its usefulness grade.We retrospectively analyzed openly available PROSTATEx dataset with 112 foci in 99 patients. In all patients, histological grading...
Abstract Fractal analysis of dynamic, four-dimensional computed tomography myocardial perfusion (4D-CTP) imaging might have potential for noninvasive differentiation microvascular ischemia and macrovascular coronary artery disease (CAD) using fractal dimension (FD) as quantitative parameter complexity. This multi-center proof-of-concept study included 30 rigorously characterized patients from the AMPLIFiED trial with nonoverlapping confirmed (n micro = 10), CAD macro or normal 10) invasive...
To investigate whether fractal analysis of perfusion differentiates hepatocellular adenoma (HCA) subtypes and carcinoma (HCC) in non-cirrhotic liver by quantifying chaos using four-dimensional dynamic contrast-enhanced magnetic resonance imaging (4D-DCE-MRI).A retrospective population 63 patients (47 female) with histopathologically characterized HCA HCC livers was investigated. Our consisted 13 hepatocyte nuclear factor (HNF)-1α-inactivated (H-HCAs), 7 β-catenin-exon-3-mutated (bex3-HCAs),...
Patient motion can degrade image quality of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) due to subtraction artifacts. By objectively and subjectively assessing the impact principal component analysis (PCA)-based registration on pretreatment DCE-MRIs breast cancer patients, we aim validate four-dimensional for DCE MRI.After applying a four-dimensional, PCA-based algorithm 154 histopathologically well-described quantitatively determined in unregistered registered images. For...
Tumour size measurement is pivotal for staging and stratifying patients with pancreatic ductal adenocarcinoma (PDA). However, computed tomography (CT) frequently underestimates tumour due to insufficient depiction of the rim. CT-derived fractal dimension (FD) maps might help visualise perfusion chaos, thus allowing more realistic measurement.In 46 histology-proven PDA, we compared measurements in routine multiphasic CT scans, FD maps, multi-parametric magnetic resonance imaging (mpMRI), and,...
Multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) assessment is sensitive but not specific for detecting clinically significant prostate cancer. This study validates the diagnostic accuracy of recently suggested fractal dimension (FD) perfusion cancer.Routine clinical MR imaging data, acquired at 3 T without an endorectal coil including dynamic contrast-enhanced sequences, 72 cancer foci in 64 patients were analyzed. In-bore MRI-guided biopsy International Society...
Objectives The mutual and intertwined dependence of inflammation angiogenesis in synovitis is widely acknowledged. However, no clinically established tool for objective quantitative assessment routinely available. This study establishes fractal analysis as a novel method to quantitatively assess inflammatory activity based on synovitis. Methods First, we pathophysiological framework including software perfusion phantoms, which allowed derive explainability with known controllable reference...
Compressed sensing allows for image reconstruction from sparsely sampled k-space data, which is particularly useful in dynamic contrast enhanced MRI (DCE-MRI). The aim of the study was to assess diagnostic value a volume-interpolated 3D T1-weighted spoiled gradient-echo sequence with variable density Cartesian undersampling and compressed (CS) head neck MRI.
Abstract Purpose Risk stratification for incidence of major adverse cardiovascular events (MACE) in patients with dialysis-dependent end-stage renal disease (dd-ESRD) is challenging. Moreover, the usefulness coronary CT angiography (CCTA) often limited because high calcification. This study aimed to investigate prognostic value comprehensive cardiac dd-ESRD predicting MACE. Materials and methods retrospective analysis included 92 who underwent CT. Obstructive artery (CAD) was defined by CCTA...
Objectives Fractal analysis of dynamic myocardial stress computed tomography perfusion imaging (4D-CTP) has shown potential to noninvasively differentiate obstructive coronary artery disease (CAD) and microvascular (CMD). This study validates fractal 4D-CTP in a multicenter setting assesses its diagnostic accuracy subgroups with ischemia nonobstructed arteries (INOCA) mild moderate stenosis. Materials Methods From the AMPLIFiED trial, patients suspected or known chronic an indication for...