Alle Papers – Medizinische Bildsegmentierung

Robust estimation of adaptive tensors of curvature by tensor voting

Automated identification and grading of coronary artery stenoses with X-ray angiography

Intensity-Based Non-rigid Registration Using Adaptive Multilevel Free-Form Deformation with an Incompressibility Constraint

Nerve optic segmentation in CT images using a deep learning model and a texture descriptor

Feature-based image registration by means of the CHC evolutionary algorithm

A multi-level thresholding approach using a hybrid optimal estimation algorithm

A Maximum Likelihood Approach to Texture Classification

Wavelet-Based Image Texture Classification Using Local Energy Histograms

Combining Single View Features and Asymmetry for Detection of Mass Lesions

M3Net: A multi-model, multi-size, and multi-view deep neural network for brain magnetic resonance image segmentation

A theory of binary digital pictures

Maximin affinity learning of image segmentation

Local segmentation of images using an improved fuzzy C-means clustering algorithm based on self-adaptive dictionary learning

Dynamic MRI Scan Plane Control for Passive Tracking of Instruments and Devices

3D shearlet-based descriptors combined with deep features for the classification of Alzheimer's disease based on MRI data

Improving CT Image Tumor Segmentation Through Deep Supervision and Attentional Gates

A new symmetry-based method for mid-sagittal plane extraction in neuroimages

Algebraic Multigrid on Unstructured Meshes

Vesselness enhancement diffusion

Fully automated brain tumour segmentation system in 3D‐MRI using symmetry analysis of brain and level sets

An interactive image segmentation method for lithological boundary detection: A rapid mapping tool for geologists

Skull stripping and automatic segmentation of brain MRI using seed growth and threshold techniques

Image Registration Using Blur-Invariant Phase Correlation

Biomedical Image Segmentation via Representative Annotation

A hierarchical local region-based sparse shape composition for liver segmentation in CT scans