A Discrete Reeb Graph Approach for the Segmentation of Human Body Scans

A topological approach for segmenting human body shape

Segmentation of 3D human body is a very challenging problem in applications exploiting human scan data. To tackle this problem, this paper proposes a topological approach based on the Discrete Reeb Graph (DRG) which is an extension of the classical Reeb Graph to handle unorganized clouds of 3D points. The essence of the approach concerns detecting critical nodes in the DRG thereby permitting th...

A Discrete Approach to Reeb Graph Computation and Surface Mesh Segmentation: Theory and Algorithm

Volumetric Segmentation of Complex Bone Structures from Medical Imaging Data Using Reeb Graphs

The exploration of medical imaging datasets often requires a segmentation of the images according to different materials or structures. Model-based algorithms excel in finding closed boundary contours enclosing the structure to be segmented. However, porose structures like Spongiosa have a complex topology and do not exhibit a unique single closed boundary contour. In order to enable segmentati...

Reeb Graphs Through Local Binary Patterns

This paper presents an approach to derive critical points of a shape, the basis of a Reeb graph, using a combination of a medial axis skeleton and features along this skeleton. A Reeb graph captures the topology of a shape. The nodes in the graph represent critical points (positions of change in the topology), while edges represent topological persistence. We present an approach to compute such...

Prostate segmentation and lesions classification in CT images using Mask R-CNN

Purpose: Non-cancerous prostate lesions such as prostate calcification, prostate enlargement, and prostate inflammation cause too many problems for men’s health. This research proposes a novel approach, a combination of image processing techniques and deep learning methods for classification and segmentation of the prostate in CT-scan images by considering the experienced physicians’ reports. ...