A study has been completed examining design issues concerning the interpretation of and dissemination of multimodal medical imaging data sets to diverse audiences. To create a model data set mouse fibrosarcoma tissue was visualised via magnetic resonance imaging (MRI), Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry (MALDI-MSI) and histology. MRI images were acquired using the 0.25T Esaote GScan; MALDI images were acquired using a Q-Star Pulsar I mass spectrometer. Histological staining of the same tissue sections used for MALDI-MSI was then carried out. Areas assigned to hemosiderin deposits due to haemorrhaging could be visualised via MRI. In the MALDI-MSI data obtained the distribution sphingomyelin species could be used to identify regions of viable tumour. Mathematical ‘up sampling’ using hierarchical clustering-based segmentation provided a sophisticated image enhancement tool for both MRI and MALDI-MS and assisted in the correlation of images.

中文翻译：

---

使用多模式成像将医学图像传达给不同的受众

已经完成了一项研究，研究了有关多模态医学成像数据集的解释和向不同受众传播的设计问题。为了创建模型数据集，通过磁共振成像（MRI），基质辅助激光解吸/电离质谱（MALDI-MSI）和组织学观察小鼠纤维肉瘤组织。使用0.25T Esaote GScan采集MRI图像；使用Q-Star Pulsar I质谱仪获取MALDI图像。然后对用于MALDI-MSI的相同组织切片进行组织学染色。可以通过MRI可视化分配给因出血引起的铁血黄素沉积物的区域。在获得的MALDI-MSI数据中，鞘磷脂分子的分布可用于鉴定有活力的肿瘤区域。