𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Generation of Point-Based 3D Statistical Shape Models for Anatomical Objects

✍ Scribed by Cristian Lorenz; Nils Krahnstöver

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
394 KB
Volume
77
Category
Article
ISSN
1077-3142

No coin nor oath required. For personal study only.

✦ Synopsis

A novel method that allows the development of surface point-based three-dimensional statistical shape models is presented. Given a set of medical objects, a statistical shape model can be obtained by principal component analysis. This technique requires that a set of complex shaped objects is represented as a set of vectors that uniquely determines the shapes of the objects and at the same time is suitable for a statistical analysis. The correspondence between the vector components and the respective shape features has to be identical in order for all shape parameter vectors to be considered. We present a novel approach to the correspondence problem for arbitrary three-dimensional objects which involves developing a template shape and fitting this template to all objects to be analyzed. The method is successfully applied to obtain a statistical shape model for the lumbar vertebrae.

📜 SIMILAR VOLUMES

PCA-based method for 3D shape recovery o
PCA-based method for 3D shape recovery of microscopic objects from image focus using discrete cosine transform
✍ Muhammad Tariq Mahmood; Wook-Jin Choi; Tae-Sun Choi 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 778 KB

## Abstract This article introduces a new algorithm for shape from focus (SFF) based on discrete cosine transform (DCT) and principal component analysis (PCA). DCT is applied on a small 3D neighborhood for each pixel in the image volume. Instead of summing all focus values in a window, AC parts of