This paper reviews the different multimodal applications based on a large ext ent of label-freeinaging modalities,ranging from linear to nonlinear optics,while also inchuding spectroscopicmeasurements.We put specific ...This paper reviews the different multimodal applications based on a large ext ent of label-freeinaging modalities,ranging from linear to nonlinear optics,while also inchuding spectroscopicmeasurements.We put specific emphasis on multimodal measurements going across the usual boundaries between imaging modalities,whereas most multimodal platforms combine techniquesbased on similar light interactions or similar hardware implementations.In this review,we limitthe scope to focus on applications for biology such as live cells or tissues,since by their nat ure ofbeing alive or fragile,we are often not free to take liberties with the image acquisition times andare forced to gather the maximum amount of information possible at one time.For such samples,imaging by a given label-free method usually presents a challenge in obt aining suficient opticalsignal or is limited in terms of the types of observable targets.Multimodal imaging is thenparticularly attractive for these samples in order to maximize the amount of measured infor-mation.While multimodal imaging is always useful in the sense of acquiring additional infor-mation from additional modes,at times it is possible to attain information that could not bediscovered using any single mode alone,which is the essence of the progress that is possible usinga multimodal approach.展开更多
基金funding from the Japan Society for the Promotionof Science(JSPS)through the Funding Program for World-Leading Innovative R&D on Science and Technology(FIR.ST Program)JSPS World Premier International Research Center Initiative Funding Program.
文摘This paper reviews the different multimodal applications based on a large ext ent of label-freeinaging modalities,ranging from linear to nonlinear optics,while also inchuding spectroscopicmeasurements.We put specific emphasis on multimodal measurements going across the usual boundaries between imaging modalities,whereas most multimodal platforms combine techniquesbased on similar light interactions or similar hardware implementations.In this review,we limitthe scope to focus on applications for biology such as live cells or tissues,since by their nat ure ofbeing alive or fragile,we are often not free to take liberties with the image acquisition times andare forced to gather the maximum amount of information possible at one time.For such samples,imaging by a given label-free method usually presents a challenge in obt aining suficient opticalsignal or is limited in terms of the types of observable targets.Multimodal imaging is thenparticularly attractive for these samples in order to maximize the amount of measured infor-mation.While multimodal imaging is always useful in the sense of acquiring additional infor-mation from additional modes,at times it is possible to attain information that could not bediscovered using any single mode alone,which is the essence of the progress that is possible usinga multimodal approach.
