Signed-distance function based non-rigid registration of image series with varying image intensity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023001%3A_____%2F21%3A00080677" target="_blank" >RIV/00023001:_____/21:00080677 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21340/21:00346092

Výsledek na webu

<a href="http://www.aimsciences.org/article/doi/10.3934/dcdss.2020386" target="_blank" >http://www.aimsciences.org/article/doi/10.3934/dcdss.2020386</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3934/dcdss.2020386" target="_blank" >10.3934/dcdss.2020386</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Signed-distance function based non-rigid registration of image series with varying image intensity

Popis výsledku v původním jazyce

In this paper we propose a method for locally adjusted optical flow-based registration of multimodal images, which uses the segmentation of object of interest and its representation by the signed-distance function (OFdist method). We deal with non-rigid registration of the image series acquired by the Modiffied Look-Locker Inversion Recovery (MOLLI) magnetic resonance imaging sequence, which is used for a pixel-wise estimation of T1 relaxation time. The spatial registration of the images within the series is necessary to compensate the patient&apos;s imperfect breath-holding. The evolution of intensities and a large variation of image contrast within the MOLLI image series, together with the myocardium of left ventricle (the object of interest) typically not being the most distinct object in the scene, makes the registration challenging. The paper describes all components of the proposed OFdist method and their implementation. The method is then compared to the performance of a standard mutual information maximization-based registration method, applied either to the original image (MIM) or to the signed-distance function (MIMdist). Several experiments with synthetic and real MOLLI images are carried out. On synthetic image with a single object, MIM performed the best, while OFdist and MIMdist provided better results on synthetic images with more than one object and on real images. When applied to signed-distance function of two objects of interest, MIMdist provided a larger registration error, but more homogeneously distributed, compared to OFdist. For the real MOLLI image series with left ventricle pre-segmented using a level-set method, the proposed OFdist registration performed the best, as is demonstrated visually and by measuring the increase of mutual information in the object of interest and its neighborhood. © 2021 American Institute of Mathematical Sciences. All rights reserved.

Název v anglickém jazyce

Signed-distance function based non-rigid registration of image series with varying image intensity

Popis výsledku anglicky

In this paper we propose a method for locally adjusted optical flow-based registration of multimodal images, which uses the segmentation of object of interest and its representation by the signed-distance function (OFdist method). We deal with non-rigid registration of the image series acquired by the Modiffied Look-Locker Inversion Recovery (MOLLI) magnetic resonance imaging sequence, which is used for a pixel-wise estimation of T1 relaxation time. The spatial registration of the images within the series is necessary to compensate the patient&apos;s imperfect breath-holding. The evolution of intensities and a large variation of image contrast within the MOLLI image series, together with the myocardium of left ventricle (the object of interest) typically not being the most distinct object in the scene, makes the registration challenging. The paper describes all components of the proposed OFdist method and their implementation. The method is then compared to the performance of a standard mutual information maximization-based registration method, applied either to the original image (MIM) or to the signed-distance function (MIMdist). Several experiments with synthetic and real MOLLI images are carried out. On synthetic image with a single object, MIM performed the best, while OFdist and MIMdist provided better results on synthetic images with more than one object and on real images. When applied to signed-distance function of two objects of interest, MIMdist provided a larger registration error, but more homogeneously distributed, compared to OFdist. For the real MOLLI image series with left ventricle pre-segmented using a level-set method, the proposed OFdist registration performed the best, as is demonstrated visually and by measuring the increase of mutual information in the object of interest and its neighborhood. © 2021 American Institute of Mathematical Sciences. All rights reserved.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30224 - Radiology, nuclear medicine and medical imaging

Projekt

<a href="/cs/project/NV19-08-00071" target="_blank" >NV19-08-00071: Analýza charakteru proudění a predikce vývoje změn v endovaskulárně ošetřených tepnách pomocí MR zobrazování a matematického modelování.</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Discrete and Continuous Dynamical Systems-Series S

ISSN

1937-1632

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

1145-1160

Kód UT WoS článku

000608373600028

EID výsledku v databázi Scopus

2-s2.0-85099694424