Mentoring

Anatomical Landmark Detection From X-Ray Images Using Convolutional Neural Networks

In this thesis, we propose an approach that robustly detects three-dimensional (3D) anatomical landmarks in two-dimensional (2D) radiography projections (X-rays). 2D X-ray images are widely used since they provide a fast and accurate assessment of …

Morphological Indicators for Limitations in Nasal Breathing

In order to better understand the relationship between shape of the nasal cavity and to find objective classification for breathing obstruction, a population of 25 cases of healthy nasal cavity and 27 cases with diagnosed nasal airway obstruction (NAO) …

Deep Learning for Boundary Detection in Model-Based Segmentation

We propose an algorithm to segment 3D medical images that combines deformable anatomical models and deep learning. The aim is to develop a method that is flexible enough to be applied to different anatomies and image modalities. To this end, we …

Geometrische Rekonstruktion von Anatomischen Strukturen des Kopfes aus Tomographischen Daten

Landmarken-basierte 2d-3d Objektpositionierung

Deformable Meshes for Accurate Automatic Segmentation of Medical Image Data

Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author’s …

Fitting Smooth Strips to Rough Surfaces

Interaktives Planungstool Zur 3D Rekonstruktion Von Knochenresektion

Articulated Statistical Shape Models

Automatic Liver Segmentation in Contrast Enhanced CT Data Using 3D Free Form Deformation Based on Optimal Graph Searching

**Background.** Liver segmentation is an important prerequisite for surgery planning. The manual segmentation of the liver is very time consuming, so it is desired to develop a method that can precisely segment the liver without any human …