Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (9): 119-127.doi: 10.11896/jsjkx.250400037

• Intelligent Medical Engineering • Previous Articles     Next Articles

Delayed PET Reconstruction for Early Tumor Diagnosis:Multimodal PET/CT Nuclear Matrix- constrained Delayed Imaging Algorithm

SONG Zhichao1,2, ZHANG Jianping3, ZHANG Qiyang2, FANG Xi1, XIE Liang1, SONG Shaoli3, HU Zhanli2   

  1. 1 School of Mathematics and Statistics,Wuhan University of Technology,Wuhan 430070,China
    2 Research Center for Medical AI,Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen,Guangdong 518055,China
    3 Department of Nuclear Medicine,Fudan University Shanghai Cancer Center,Shanghai 200032,China
  • Received:2025-04-09 Revised:2025-06-20 Online:2025-09-15 Published:2025-09-11
  • About author:SONG Zhichao,born in 1999,postgra-duate.Her main research interests include medical image processing and survival analysis.
    SONG Shaoli,born in 1972,Ph.D,chief physician,recipient of Shanghai Leading Talents(2023).Her main research interest is basic and cinical research in nuclear medicine of tumors.
  • Supported by:
    National Natural Science Foudation of China(82372038).

PDF (PC)

13

Abstract: Positron emission tomography(PET) delayed imaging is of great significance in tumor heterogeneity analysis and treatment evaluation,but its clinical application is limited by low resolution,high noise and inaccurate quantification.Computed tomography(CT) can provide high-resolution anatomical information,but lacks functional information in tumor assessment,making it difficult to distinguish benign and malignant lesions and evaluate metabolic activity.Although dynamic PET/CT fusion can improve image quality,multiple CT scans increase patient radiation exposure and are not conducive to long-term follow-up.To address the above problems,a super-resolution enhanced PET/CT multimodal kernel matrix constraint algorithm(SR-PET/CT-KMC) is proposed.The algorithm super-enhances the initial scan PET image based on stable diffusion,combines it with the anatomical prior information of the initial scan CT image,and establishes an expectation maximization(EM) iterative framework for multimodal PET/CT kernel matrix constraints.Stable diffusion is used to improve the resolution of the initial scan PET,while the multimodal PET/CT prior information is used to suppress noise and artifacts.By utilizing the structural information of the initial scan CT,the need for CT scans in delayed imaging is reduced,thereby reducing the patient’s cumulative radiation exposure.Experimental results show that compared with PET-KEM,the peak signal-to-noise ratio(PSNR) of SR-PET/CT-KMC is improved by 6.23%,the structural similarity index(SSIM) is improved by 9.64%,the normalized root mean square error(NRMSE) is reduced by 33.3%,and the mean square error(MSE) is reduced by 13.92%.Compared with CT-KEM,the PSNR is improved by 4.05%,the SSIM is improved by 1.11%,the NRMSE is reduced by 33.3%,and the MSE is reduced by 8.11%.These results show that this method has advantages in improving the resolution and quantitative accuracy of delayed scanning PET images,providing a new imaging paradigm for tumor metabolism tracking and improving the clinical feasibility of delayed PET imaging.

Key words: Delayed imaging, Super-resolution PET, Multi-modal kernel matrix, Biomedical, Kernel method

CLC Number: 

  • TP391.41
[1]STAFFORD W C,PENG X,OLOFSSON M H,et al.Irreversible inhibition of cytosolic thioredoxin reductase 1 as a mechanistic basis for anticancer therapy[J].Science Translational Medicine,2018,10(428):eaaf7444.
[2]SCHWENCK J,SONANINI D,COTTON J M,et al.Advances in PET imaging of cancer[J].Nature Reviews Cancer,2023,23(7):474-490.
[3]CROTEAU E,RENAUD J M,RICHARD M A,et al.PET Metabolic Biomarkers for Cancer:Supplementary Issue:Biomarkers and their Essential Role in the Development of Personalised Therapies(A)[J].Biomarkers in cancer,2016,8:BIC.S27483.
[4]GRASSO V,WILLUMEIT-RÖMER R,JOSE J.Superpixelspectral unmixing framework for the volumetric assessment of tissue chromophores:A photoacoustic data-driven approach[J].Photoacoustics,2022,26:100367.
[5]KHARE S K,MARCH S,BARUA P D,et al.Application of data fusion for automated detection of children with developmental and mental disorders:A systematic review of the last decade[J].Information Fusion,2023,99:101898.
[6]BAGCI U,UDUPA J K,MENDHIRATTA N,et al.Joint segmentation of anatomical and functional images:Applications in quantification of lesions from PET,PET-CT,MRI-PET,and MRI-PET-CT images[J].Medical Image Analysis,2013,17(8):929-945.
[7]BONNEY L M,KALISVAART G M,VAN VELDEN F H P,et al.Deep learning image enhancement algorithms in PET/CT imaging:a phantom and sarcoma patient radiomic evaluation[J].European Journal of Nuclear Medicine and Molecular Imaging,2025:1-12.
[8]DIMITRAKOPOULOU-STRAUSS A,PAN L,SACHPEKIDISC.Kinetic modeling and parametric imaging with dynamic PET for oncological applications:general considerations,current clinical applications,and future perspectives[J].European journal of nuclear medicine and molecular imaging,2021,48:21-39.
[9]ZONDERVAN R L,HAHN P F,SADOW C A,et al.Frequent body CT scanning of young adults:indications,outcomes,and risk for radiation-induced cancer[J].Journal of the American College of Radiology,2011,8(7):501-507.
[10]MATAAC M T,LI X,REHANI M M.What proportion of CT scan patients are alive or deceased after 10 years?[J].European Journal of Radiology,2024,178:111629.
[11]ALBERTS I,SARI H,MINGELS C,et al.Long-axial field-of-view PET/CT:perspectives and review of a revolutionary development in nuclear medicine based on clinical experience in over 7000 patients[J].Cancer Imaging,2023,23(1):28.
[12]MOSTAFAPOUR S,GREUTER M,VAN SNICK J H,et al.Ultra-low dose CT scanning for PET/CT[J].Medical Physics,2024,51(1):139-155.
[13]SHEN C,TIE C,YANG Z,et al.Bidirectional condition diffu-sion probabilistic models for pet image denoising[J].IEEE Transactions on Radiation and Plasma Medical Sciences,2024,8(4):402-415.
[14]WANG J,YUE Z,ZHOU S,et al.Exploiting diffusion prior for real-world image super-resolution[J].International Journal of Computer Vision,2024,132(12):5929-5949.
[15]AI X,HUANG B,CHEN F,et al.RED:Residual estimation diffusion for low-dose PET sinogram reconstruction[J].Medical Image Analysis,2025,102:103558.
[16]ZHANG Q,HU Y,ZHOU C,et al.Reducing pediatric total-body PET/CT imaging scan time with multimodal artificial intelligence technology[J].European Journal of Nuclear Medicine and Molecular Imaging physics,2024,11(1):1.
[17]FILIPOVIĆ M,BARAT E,DAUTREMER T,et al.PET reconstruction of the posterior image probability,including multimodal images[J].IEEE Transactions on Medical Imaging,2018,38(7):1643-1654.
[18]ZAIDI H,BECKER M.The promise of hybrid PET\/MRI:technical advances and clinical applications[J].IEEE Signal Processing Magazine,2016,33(3):67-85.
[19]CHEN Z,LIU Y,ZHANG Y,et al.Enhanced Multimodal Low-rank Embedding based Feature Selection Model for Multimodal Alzheimer’s Disease Diagnosis[J].IEEE Transactions on Medical Imaging,2025,44(2):815-827.
[20]WANG G,QI J.PET image reconstruction using kernel method[J].IEEE Transactions on Medical Imaging,2014,34(1):61-71.
[21]MULLER F M,LI E J,DAUBE-WITHERSPOON M E,et al.Impact of deep learning denoising on kinetic modelling for low-dose dynamic PET:application to single-and dual-tracer imaging protocols[J].European Journal of Nuclear Medicine and Mole-cular Imaging,2025:1-19.
[22]ZHOU S,CHAN K,LI C,et al.Towards robust blind face restoration with codebook lookup transformer[J].Advances in Neural Information Processing Systems,2022,35:30599-30611.
[23]DRAELOS R L,DOV D,MAZUROWSKI M A,et al.Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes[J].Medical Image Analysis,2021,67:101857.
[24]NUYTS J,MICHEL C,DUPONT P.Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations[J].IEEE Transactions on Medical Imaging,2001,20(5):365-375.
[25]HU R,CUI J,LI C,et al.Dynamic low-count PET image reconstruction using spatio-temporal primal dual network[J].Physics in Medicine & Biology,2023,68(13):135015.
[1] XU Jian-min, SUN Peng, WU Shu-fang. Microblog Rumor Detection Method Based on Propagation Path Tree Kernel Learning [J]. Computer Science, 2022, 49(6): 342-349.
[2] WANG Zhong-yuan, LIU Jing-lei. Kernel Subspace Clustering Based on Second-order Neighbors [J]. Computer Science, 2021, 48(6): 86-95.
[3] ZHU Ying-wen, YANG Jun. Euler Kernel-based Data Stream Clustering Algorithm [J]. Computer Science, 2019, 46(12): 74-82.
[4] GONG Qu and XU Kai-qiang. Parameter-less Supervised Kernel Locality Preserving Projection and Face Recognition [J]. Computer Science, 2016, 43(9): 301-304.
[5] ZHENG Jian-wei, KONG Chen-chen, WANG Wan-liang, QIU Hong and ZHANG Hang-ke. Kernel-based Supervised Neighborhood Projection Analysis Algorithm [J]. Computer Science, 2016, 43(6): 312-315.
[6] WEI Xiao-mei, HUANG Yu, CHEN Bo and JI Dong-hong. Research on Tagging Biomedical Event Trigger [J]. Computer Science, 2015, 42(10): 239-243.
[7] WANG Pei-yan and CAI Dong-feng. Distance-based Kernel Evaluation Measure [J]. Computer Science, 2014, 41(2): 72-75.
[8] ZENG Ya-jie,YANG Xin,XU Hong-wei,LIU Yang,LIANG Hua-geng and DING Ming-yue. Research on Ultrasound Carotid Image Segmentation Methods Based on Local Chan-Vese Model Using Level Set Method [J]. Computer Science, 2013, 40(Z11): 304-308.
[9] . Face Feature Extraction Based on Weighted Multiple Kernel Fisher Discriminant Analysis [J]. Computer Science, 2012, 39(9): 262-265.
[10] FANG Yi-min,ZHANG Ling,SUN Wei-min,XU Bao-guo. SMO Algorithm for Resolving Huber-SVR with Non-positive Kernels [J]. Computer Science, 2010, 37(7): 212-216.
[11] . [J]. Computer Science, 2009, 36(3): 156-157.
[12] . [J]. Computer Science, 2008, 35(12): 190-191.
[13] JIA Lei LIAO Shi-zhong （School of Computer Science and Technology,Tianjin University,Tianjin 300072,China）. [J]. Computer Science, 2008, 35(12): 148-150.
[14] . [J]. Computer Science, 2007, 34(9): 131-134.
[15] . [J]. Computer Science, 2006, 33(6): 172-174.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.