Pilot implementation of a sonography simulator in gynecological medical training and continuing education: A practical report.

Objective: In addition to patient consent, learning sonography requires considerable time and personnel resources. To implement patient-friendly and resource-saving ultrasound teaching, a comprehensively equipped sonography simulator (SoSim) was purchased at the Medical Interprofessional Training Centre (MITZ) of the Faculty of Medicine at TU Dresden. In a first step, the SoSim training was trialed in a sample (n=5) in cooperation with the Clinic and Polyclinic for Gynecology and Obstetrics at Dresden University Hospital (GYN).

Characterization of human placental fetal vessels in gestational diabetes mellitus.

Gestational diabetes mellitus is one of the most common complications during pregnancy. Its prevalence is rapidly increasing worldwide. Gestational diabetes mellitus is leading to an elevated risk for the development of endothelial dysfunction and cardiovascular diseases both in the mother and the child in later life.

Deep-DM: Deep-driven deformable model for 3D image segmentation using limited data.

Objective - Medical image segmentation is essential for several clinical tasks, including diagnosis, surgical and treatment planning, and image-guided interventions. Deep Learning (DL) methods have become the state-of-the-art for several image segmentation scenarios. However, a large and well-annotated dataset is required to effectively train a DL model, which is usually difficult to obtain in clinical practice, especially for 3D images.