3D Statistical Shape Model Building using Consistent Parameterization

نویسندگان

  • Matthias Kirschner
  • Stefan Wesarg
چکیده

We propose a new correspondence optimisation algorithm for building 3D statistical shape models (SSMs) of genus-0 shapes. The main contribution of our work is the use of parameter space propagation to generate consistent spherical parameterisations of the training shapes. We present evaluation results for two data sets: A set of 30 liver shapes from different patients, and a set of 25 left ventricles covering the cardiac cycle of a single patient. Our evaluation shows that the use of parameter space propagation improves the robustness of correspondence optimisation algorithms and lead to fast convergence times.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimal Initialization for 3D Correspondence Optimization: An Evaluation Study

The identification of corresponding landmarks across a set of training shapes is a prerequisite for statistical shape model (SSM) construction. We automatically establish 3D correspondence using one new and several known alternative approaches for consistent, shape-preserving, spherical parameterization. The initial correspondence determined by all employed methods is refined by optimizing a gr...

متن کامل

Parameterization of 3D Brain Structures for Statistical Shape Analysis

Statistical Shape Analysis (SSA) is a powerful tool for noninvasive studies of pathophysiology and diagnosis of brain diseases. It also provides a shape constraint for the segmentation of brain structures. There are two key problems in SSA: the representation of shapes and their alignments. The widely used parameterized representations are obtained by preserving angles or areas and the alignmen...

متن کامل

Automatic Generation of 3D Statistical Shape Models of the Knee Bones

We are working on generating an accurate Statistical Map of the Knee bones and Cartilages for use as ‘a-priori’ knowledge in segmentation algorithms. The approach we are presenting to automatically generate 3D Statistical Shape Models is based on the Point Distribution Model optimisation framework of Davies et al [8]. Our scheme uses a conformal parameterization with an Eigenspace objective fun...

متن کامل

Construction of groupwise consistent shape parameterizations by propagation

Prior knowledge can highly improve the accuracy of segmentation algorithms for 3D medical images. A popular method for describing the variability of shape of organs are statistical shape models. One of the greatest challenges in statistical shape modeling is to compute a representation of the training shapes as vectors of corresponding landmarks, which is required to train the model. Many algor...

متن کامل

Statistical Shape Analysis for Computer Aided Spine Deformity Detection

In this paper we describe a medical application where we exploit surface properties (measured in form of 3D-Range scans of the human back) to derive a-priori unknown additional properties of the proband, that otherwise can only be acquired using multiple x-ray recordings or volumetric scans as CT or MRI. On the basis of 274 data sets, we perform classification using statistical shape analysis m...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010