Laura M. Cole, Arul N. Selvan, Rebecca Partridge, Heath Reed, Chris Wright, Malcolm R. Clench
{"title":"利用多模态成像技术向不同受众传播医学图像","authors":"Laura M. Cole, Arul N. Selvan, Rebecca Partridge, Heath Reed, Chris Wright, Malcolm R. Clench","doi":"10.1186/s40679-015-0012-8","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":460,"journal":{"name":"Advanced Structural and Chemical Imaging","volume":"1 1","pages":""},"PeriodicalIF":3.5600,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40679-015-0012-8","citationCount":"2","resultStr":"{\"title\":\"Communication of medical images to diverse audiences using multimodal imaging\",\"authors\":\"Laura M. Cole, Arul N. Selvan, Rebecca Partridge, Heath Reed, Chris Wright, Malcolm R. Clench\",\"doi\":\"10.1186/s40679-015-0012-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":460,\"journal\":{\"name\":\"Advanced Structural and Chemical Imaging\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5600,\"publicationDate\":\"2015-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/s40679-015-0012-8\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Structural and Chemical Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s40679-015-0012-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Structural and Chemical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s40679-015-0012-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Communication of medical images to diverse audiences using multimodal imaging
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.