CAJ | 학술논문

在大脑磁共振成像(MRI)影像学的数据采集中，通常先扫描一幅定位图像，并根据解剖学先验知识手动调整合适的扫描定位参数，再进行后续的正式扫描．该文实现了一种直接以大脑模板为参照的自动定位的方法：首先采集一幅中等分辨率的快速三维定位图像，然后通过与模板的配准确定定位参数，并应用到后续序列的扫描，以保证不同被试在图像采集时采用与模板一致的空间定位．该方法一方面便于不同被试的图像数据之间进行系统性比较与参照，帮助诊断者快速定位病灶，也可在后续常用的基于体素分析过程最大化数据的利用效率．另一方面，针对单个体多次扫描之间的自动定位，该文进一步使用迭代方法，通过多次“扫描、配准、自动定位”步骤，逐步减小图像配准算法的误差．实验证明，该文基于大脑模板的自动定位方法能够确保不同被试之间和同一被试之内在图像数据采集时的空间定位高度一致性，其中同一被试内多次扫描的空间定位误差<1.0 mm和1.0o．
재대뇌자공진성상(MRI)영상학적수거채집중，통상선소묘일폭정위도상，병근거해부학선험지식수동조정합괄적소묘정위삼수，재진행후속적정식소묘．해문실현료일충직접이대뇌모판위삼조적자동정위적방법：수선채집일폭중등분변솔적쾌속삼유정위도상，연후통과여모판적배준학정정위삼수，병응용도후속서렬적소묘，이보증불동피시재도상채집시채용여모판일치적공간정위．해방법일방면편우불동피시적도상수거지간진행계통성비교여삼조，방조진단자쾌속정위병조，야가재후속상용적기우체소분석과정최대화수거적이용효솔．령일방면，침대단개체다차소묘지간적자동정위，해문진일보사용질대방법，통과다차“소묘、배준、자동정위”보취，축보감소도상배준산법적오차．실험증명，해문기우대뇌모판적자동정위방법능구학보불동피시지간화동일피시지내재도상수거채집시적공간정위고도일치성，기중동일피시내다차소묘적공간정위오차<1.0 mm화1.0o．
Acquisition of brain magnetic resonance imaging (MRI) data usually starts with a localizer for properly positioning the field of view based on a prior knowledge of brain anatomy and setting corresponding localization parameters for subsequent scans. We propose an automatic localization method that references directly to the brain atlas. The procedure first quickly acquires a 3D localization image at a median spatial resolution, and then calculates its registration parameter to the atlas and uses these parameters to position the subsequent scans, which therefore ensures the scanning configurations for different subjects are consistent with the atlas. The proposed method benefits inter-subject comparisons and referencing, in that it can help investigators locating abnormal structure, tumors or other regions-of-interest more quickly and easily, and therefore using the data in voxel based analysis more efficiently. We also propose an iterative method for automatic localizing individual subject in multiple independent follow-up scans. By iterating “scan, registration, automatic localization” steps several passes, it progressively minimizes the error of the image registration algorithm. Experiments showed that our atlas-based automatic localization method achieved high consistency of spatial location both in imaging data acquired from different subjects and in multiple separate scans from a single subject, and the localization error between multiple scans of a single subject was less than 1.0 mm and 1.0 degree.