Maximilian Lindholz

Diving deep into uterine layers: ADC and IVIM at 0.55-T MRI

Abstract Objective To investigate and analyze the microstructure of uterine layers and to evaluate the feasibility and physiological variability of uterine diffusion metrics at 0.55-T MRI in healthy volunteers and participants with adenomyosis. Materials and methods In this prosp...

Topogram-based anatomical labelling of CT series: anatomy-aware CT data processing using deep learning

Abstract Objectives This study provides a Rapid Analysis and Processing of Image Data (RAPID) framework that combines deep learning-based CT topogram analysis with DICOM spatial geometry to enable reliable anatomical labelling of CT series independent of inconsistent textual meta...