Spatially-constrained Keypoint Matching for Efficient Statistical Shape Modelling
Statistical shape models (SSMs) allow the compact description of the variability of object shapes within a given sample set. They are commonly used in medical imaging to model and analyse the shape of anatomical structures such as organs. The generation of a SSM mainly consists of the calculation of...
Saved in:
Main Authors: | Harkämper Lena, Großbröhmer Christoph, Himstedt Marian |
---|---|
Format: | Article |
Language: | English |
Published: |
De Gruyter
2024-09-01
|
Series: | Current Directions in Biomedical Engineering |
Subjects: | |
Online Access: | https://doi.org/10.1515/cdbme-2024-1051 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Weakly-Supervised Deep Shape-From-Template
by: Sara Luengo-Sanchez, et al.
Published: (2025-01-01) -
Novel image registration algorithm for scene-matching navigation
by: Hongrui YANG, et al.
Published: (2025-03-01) -
Analysis of Drought Spatial Statistics in Iran
by: saeed javizadeh, et al.
Published: (2019-06-01) -
Robust machine learning based Intrusion detection system using simple statistical techniques in feature selection
by: Sunil Kaushik, et al.
Published: (2025-02-01) -
Born Dead or Alive? Revisiting the Definition of Stillbirths in Norway
by: Hilde Leikny Sommerseth
Published: (2021-03-01)