Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA

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Hauptverfasser: Tang, Shaojie, Miao, Penpen, Gao, Xingyu, Zhong, Yu, Zhu, Dantong, Wen, Haixing, Xu, Zhihui, Wei, Qiuyue, Yao, Hongping, Huang, Xin, Gao, Rui, Zhao, Chen, Zhou, Weihua
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Veröffentlicht: 2024
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author Tang, Shaojie
Miao, Penpen
Gao, Xingyu
Zhong, Yu
Zhu, Dantong
Wen, Haixing
Xu, Zhihui
Wei, Qiuyue
Yao, Hongping
Huang, Xin
Gao, Rui
Zhao, Chen
Zhou, Weihua
author_facet Tang, Shaojie
Miao, Penpen
Gao, Xingyu
Zhong, Yu
Zhu, Dantong
Wen, Haixing
Xu, Zhihui
Wei, Qiuyue
Yao, Hongping
Huang, Xin
Gao, Rui
Zhao, Chen
Zhou, Weihua
contents A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) and cardiac computed tomography angiograms (CTA). Firstly, the left ventricle (LV) epicardial regions (LVERs) in SPECT and CTA images were segmented by using different U-Net neural networks trained to generate the point clouds of the LV epicardial contours (LVECs). Secondly, according to the characteristics of cardiac anatomy, the special points of anterior and posterior interventricular grooves (APIGs) were manually marked in both SPECT and CTA image volumes. Thirdly, we developed an in-house program for coarsely registering the special points of APIGs to ensure a correct cardiac orientation alignment between SPECT and CTA images. Fourthly, we employed ICP, SICP or CPD algorithm to achieve a fine registration for the point clouds (together with the special points of APIGs) of the LV epicardial surfaces (LVERs) in SPECT and CTA images. Finally, the image fusion between SPECT and CTA was realized after the fine registration. The experimental results showed that the cardiac orientation was aligned well and the mean distance error of the optimal registration method (CPD with affine transform) was consistently less than 3 mm. The proposed method could effectively fuse the structures from cardiac CTA and SPECT functional images, and demonstrated a potential in assisting in accurate diagnosis of cardiac diseases by combining complementary advantages of the two imaging modalities.
format Preprint
id arxiv_https___arxiv_org_abs_2402_06841
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA
Tang, Shaojie
Miao, Penpen
Gao, Xingyu
Zhong, Yu
Zhu, Dantong
Wen, Haixing
Xu, Zhihui
Wei, Qiuyue
Yao, Hongping
Huang, Xin
Gao, Rui
Zhao, Chen
Zhou, Weihua
Image and Video Processing
Computer Vision and Pattern Recognition
A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) and cardiac computed tomography angiograms (CTA). Firstly, the left ventricle (LV) epicardial regions (LVERs) in SPECT and CTA images were segmented by using different U-Net neural networks trained to generate the point clouds of the LV epicardial contours (LVECs). Secondly, according to the characteristics of cardiac anatomy, the special points of anterior and posterior interventricular grooves (APIGs) were manually marked in both SPECT and CTA image volumes. Thirdly, we developed an in-house program for coarsely registering the special points of APIGs to ensure a correct cardiac orientation alignment between SPECT and CTA images. Fourthly, we employed ICP, SICP or CPD algorithm to achieve a fine registration for the point clouds (together with the special points of APIGs) of the LV epicardial surfaces (LVERs) in SPECT and CTA images. Finally, the image fusion between SPECT and CTA was realized after the fine registration. The experimental results showed that the cardiac orientation was aligned well and the mean distance error of the optimal registration method (CPD with affine transform) was consistently less than 3 mm. The proposed method could effectively fuse the structures from cardiac CTA and SPECT functional images, and demonstrated a potential in assisting in accurate diagnosis of cardiac diseases by combining complementary advantages of the two imaging modalities.
title Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA
topic Image and Video Processing
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2402.06841