{
    "abstract": "Among numerous medical imaging modalities, diffusion weighted imaging (DWI) is extremely sensitive to acute ischemic stroke lesions, especially small infarcts. However, magnetic resonance imaging is time-consuming and expensive, and it is also prone to interference from metal implants. Therefore, the aim of this study is to design a medical image synthesis method based on generative adversarial network, Stroke-p2pHD, for synthesizing DWI images from computed tomography (CT). Stroke-p2pHD consisted of a generator that effectively fused local image features and global context information (Global_to_Local) and a multi-scale discriminator (M \n\u5728\u4f17\u591a\u533b\u5b66\u5f71\u50cf\u6a21\u6001\u4e2d\uff0c\u78c1\u5171\u632f\u6269\u6563\u52a0\u6743\u6210\u50cf\uff08DWI\uff09\u5bf9\u6025\u6027\u7f3a\u8840\u6027\u8111\u5352\u4e2d\u75c5\u53d8\uff0c\u5c24\u5176\u662f\u5c0f\u6897\u6b7b\u7076\u6781\u4e3a\u654f\u611f\u3002\u7136\u800c\uff0c\u78c1\u5171\u632f\u6210\u50cf\u8017\u65f6\u3001\u6602\u8d35\uff0c\u800c\u4e14\u5bb9\u6613\u53d7\u5230\u91d1\u5c5e\u690d\u5165\u7269\u7684\u5e72\u6270\u3002\u56e0\u6b64\uff0c\u672c\u7814\u7a76\u7684\u76ee\u7684\u662f\u8bbe\u8ba1\u4e00\u79cd\u57fa\u4e8e\u751f\u6210\u5bf9\u6297\u7f51\u7edc\u7684\u533b\u5b66\u56fe\u50cf\u5408\u6210\u65b9\u6cd5Stroke-p2pHD\uff0c\u7528\u4e8e\u4ece\u8ba1\u7b97\u673a\u65ad\u5c42\u626b\u63cf\uff08CT\uff09\u5408\u6210DWI\u56fe\u50cf\u3002Stroke-p2pHD\u5305\u542b\u6709\u6548\u878d\u5408\u56fe\u50cf\u5c40\u90e8\u7279\u5f81\u548c\u5168\u5c40\u4e0a\u4e0b\u6587\u4fe1\u606f\uff08Global_to_Local\uff09\u7684\u751f\u6210\u5668\u548c\u591a\u5c3a\u5ea6\uff08M ",
    "authors": [
        {
            "affiliation": "School of Computer and Control Engineering, Yantai University, Yantai, Shandong 264005, P. R. China.",
            "firstname": "Qing",
            "initials": "Q",
            "lastname": "Wang"
        },
        {
            "affiliation": "Department of Radiology, Yantaishan Hospital, Yantai, Shandong 264001, P. R. China.",
            "firstname": "Xinyao",
            "initials": "X",
            "lastname": "Zhao"
        },
        {
            "affiliation": "Department of Radiology, Muping District Hospital of Traditional Chinese Medicine, Yantai, Shandong 264100, P. R. China.",
            "firstname": "Xinyue",
            "initials": "X",
            "lastname": "Liu"
        },
        {
            "affiliation": "Department of Radiology, Muping District Hospital of Traditional Chinese Medicine, Yantai, Shandong 264100, P. R. China.",
            "firstname": "Zhimeng",
            "initials": "Z",
            "lastname": "Zou"
        },
        {
            "affiliation": "School of Computer and Control Engineering, Yantai University, Yantai, Shandong 264005, P. R. China.",
            "firstname": "Haiwang",
            "initials": "H",
            "lastname": "Nan"
        },
        {
            "affiliation": "School of Computer and Control Engineering, Yantai University, Yantai, Shandong 264005, P. R. China.",
            "firstname": "Qiang",
            "initials": "Q",
            "lastname": "Zheng"
        }
    ],
    "conclusions": null,
    "copyrights": null,
    "doi": "10.7507/1001-5515.202407017",
    "journal": "Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi",
    "keywords": [
        "Computed tomography (CT)",
        "Deep learning",
        "Diffusion weighted imaging (DWI)",
        "Generative adversarial networks",
        "Image synthesis"
    ],
    "methods": null,
    "publication_date": "2025-04-28",
    "pubmed_id": "40288966",
    "results": null,
    "title": "[Stroke-p2pHD: Cross-modality generation model of cerebral infarction from CT to DWI images].",
    "xml": "<Element 'PubmedArticle' at 0x78850558b740>"
}