Spatio-temporal Alignment of 4D Cardiac MR Images

نویسندگان

  • Dimitrios Perperidis
  • Anil Rao
  • Maria Lorenzo-Valdés
  • Raad Mohiaddin
  • Daniel Rueckert
چکیده

A 4D registration method for the spatio-temporal alignment of cardiac MR image sequences has been developed. The registration algorithm has the ability not only to correct any spatial misalignment between the image sequences but also any temporal misalignment which maybe the result of differences in the cardiac cycle between subjects and differences in the temporal acquisition parameters. The algorithm uses a 4D transformation model which is separated into a spatial and a temporal component: the spatial component is a 3D affine transformation which corrects for any misalignment between the two image sequences. The temporal component uses an affine transformation which corrects the temporal misalignment caused by differences in the initial acquisition offset and length of the two cardiac cycles. The method was applied to seven cardiac MR imag e sequences from healthy volunteers. The registration was qualitat ively evaluated by visual inspection and quantitatively by measuring the volume difference and overlap of anatomical regions between the sequen ces. The results indicated a significant improvement in the spatio-temporal alignment of the sequences.

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

Spatio-Temporal Free-Form Registration of Cardiac MR Image Sequences

In this paper we present two registration algorithms for the spatio-temporal alignment of cardiac MR image sequences. Both algorithms have the ability to correct spatial misalignment between the images sequences caused by global and local shape differences. In addition, they have the ability to correct temporal misalignment caused by differences in the length of the cardiac cycles and by differ...

متن کامل

Layered Spatio-temporal Forests for Left Ventricle Segmentation from 4D Cardiac MRI Data

In this paper we present a new method for fully automatic left ventricle segmentation from 4D cardiac MR datasets. To deal with the diverse dataset, we propose a fully automatic machine learning approach using two layers of spatio-temporal decision forests with almost no assumptions on the data or segmentation problem. We introduce 3D spatio-temporal features to classi cation with decision fore...

متن کامل

4D Endocardial Segmentation Using Spatio-temporal Appearance Models and Level Sets

In this paper a framework for the segmentation of cardiac MR image sequences using spatio-temporal appearance models is presented. The method splits the 4D space into 2 separate subspaces, one for changes in appearance and one subspace for changes in motion. Using the 4D appearance models in combination with a level set framework combines the robustness of model based segmentation with the flex...

متن کامل

UNIVERSITÉ DE MONTRÉAL ÉCOLE POLYTECHNIQUE DE MONTRÉAL Proposition de recherche FUSION OF MULTIMODAL CARDIAC IMAGE SEQUENCES

A major limitation of cardiac interventions is the understanding of the heart anatomy on medical images. The quality of interventional images is generally poor compared to preoperative scans such as 3D CT (Computed Tomography) or MR (Magnetic Resonance). Image processing algorithms digest and combine information from different data-sets acquired prior to and during intervention. They can isolat...

متن کامل

Spatio-temporal (2D+T) non-rigid registration of real-time 3D echocardiography and cardiovascular MR image sequences.

In this paper we describe a method to non-rigidly co-register a 2D slice sequence from real-time 3D echocardiography with a 2D cardiovascular MR image sequence. This is challenging because the imaging modalities have different spatial and temporal resolution. Non-rigid registration is required for accurate alignment due to imprecision of cardiac gating and natural motion variations between card...

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 2003