Content-Based Retrieval of Multimodal Medical Images

IRI-9527982 Wong，Stephen University of California-San弗朗西斯科$49，666 - 12个月 基于内容的多模型医学图像检索 医学图像是患者诊断、治疗、手术计划、结果评估和医学教育的核心。 然而，他们提出了最严格的要求，在未来的多媒体医疗环境中的信息管理。 因此，本研究将探索基于内容的多模态医学图像检索的新技术，包括磁共振成像（MRI），正电子发射断层扫描（PET），磁共振波谱（MRS），脑磁图（MEG），以及补充的文本报告和图像注释。 术语“内容”是一般意义上的，包括图像中的特定对象的结构和功能背景、对象本身及其三维解剖结构、以及甚至它们在不同种类的医学图像上的语义关系。 该探索性研究的成功，将为未来多媒体医疗信息系统的建设提供关键技术要素，为医学数字图书馆的发展开辟新的前景。

IRI-9527982 Wong, Stephen University of California-San Francisco $49,666 - 12 mos SGER: content-Based Retrieval of Multimodel Medical Images Medical images are at the heart of patient's diagnosis, therapy treatment, surgical planning, outcome assessment, and medical education. They, however, impose the most stringent requirements of information management in the future multimedia healthcare environments. Accordingly, this research will explore new techniques of content-based retrieval of multimodal medical images, including magnetic resonance imaging (MRI), positron emission tomography (PET), magnetic resonance spectroscopy (MRS), and magnetoencephalography (MEG), as well as complemented textual reports and image annotations. The term "content" is in a general sense, including structural and functional contexts of particular objects in an image, the objects themselves and their three dimensional anatomical structure, and even their semantic relationships across different kinds of medical images. The success of this exploratory research will provide key technical ingredients to construct future multimedia healthcare information systems and open up new vistas for digital medical library.