分子影像学杂志2026，Vol.49Issue(2)：154-160,7.DOI:10.12122/j.issn.1674-4500.2026.02.03
基于注意力门增强机制的脑钙化成分跨模态图像生成:一种MRI到CT的精准映射方法
Attention gate-enhanced cross-modal image generation for brain calcification components:a precise MRI-to-CT mapping method
摘要
Abstract
Objective To investigate an attention gate-enhanced adversarial-pixel-structural consistency(AG-APS)model for synthesizing high-quality synthetic CT(sCT)images from magnetic resonance images,enabling precise generation of intracranial calcification components.Methods A total of 134 subjects with intracranial calcifications,including both physiological and pathological cases,were retrospectively collected from Nanfang Hospital and Nanfang Hospital Zengcheng Branch of Southern Medical University from January 2022 to December 2024.In total,1478 paired axial MR-CT slices were obtained.An AG-APS model was proposed by incorporating attention gate(AG)modules into the generator.The quality of the generated sCT images was quantitatively evaluated against real CT(rCT)using mean absolute error(MAE),peak signal-to-noise ratio(PSNR),and structural similarity index(SSIM),and compared with CycleGAN,U-Net,Pix2Pix,and LSeSim.Ablation experiments were conducted,and statistical analyses were performed.Results In the whole-image synthesis task,the AG-APS achieved superior performance(MAE=0.032,PSNR=21.352 dB,SSIM=0.821)compared with U-Net,Pix2Pix,LSeSim,and CycleGAN(P<0.05),demonstrating the best overall performance.For local evaluation of calcified regions,AG-APS also outperformed competing methods in image quality,structural fidelity,and textural consistency(MAE=0.102,PSNR=32.360 dB,SSIM=0.986),with significant improvements(P<0.05).In false-positive detection of calcification regions,the false-positive rate(FPR)was 2.11%and 0%when tolerance thresholds were set at 5%and 10%,respectively.Furthermore,ablation studies confirmed the effectiveness and necessity of introducing the AG module into the generator for enhancing synthesis quality.Conclusion The AG-APS model enables high-quality sCT generation from brain MR images,achieving precise reconstruction of intracranial calcifications.This approach facilitates calcification identification,reduces reliance on CT imaging,and lowers radiation exposure,underscoring its strong clinical potential.关键词
钙化/生成对抗网络/跨模态重建/注意力机制/计算机断层扫描/磁共振成像Key words
calcification/generative adversarial networks/cross-modality reconstruction/attention mechanism/computed tomography/magnetic resonance imaging引用本文复制引用
吕祎君,贾铭,曾伟雄,林嘉泽,陈丽华,钟俊远,钟海舰,秦耿耿..基于注意力门增强机制的脑钙化成分跨模态图像生成:一种MRI到CT的精准映射方法[J].分子影像学杂志,2026,49(2):154-160,7.基金项目
国家自然科学基金(32571282) （32571282）
广东省自然科学基金(2024A1515011520) （2024A1515011520）
广东省省级科技计划项目(2024A1111120015) （2024A1111120015）
赣州市科技计划项目(2022-RC1349、2022-ZD1373)Supported by National Natural Science Foundation of China(32571282) （2022-RC1349、2022-ZD1373）
