11/25/2023 0 Comments Thebrain 9 import outline14 completed the registration of two-dimensional microscopy images to MRI data by manually extracting feature points, but their number was limited and subjective. 20 used automatic methods to extract feature points and achieved the registration of histopathological data, but the accuracy of the automatic recognition methods used was greatly affected by image quality. ![]() 17 combined the benefits of artificial and automatic methods and achieved the registration of two-dimensional continuous microscopy images to a brain atlas. Briefly, when neuroscientists are struggling to obtain a valuable experimental dataset, they often find that it is difficult to extract sufficient feature points accurately to ensure the registration quality.Īnother challenge occurs with the TB-scale large-volume whole-brain datasets brought by imaging at the cellular level. Generally, the registration tools such as ITK that are widely used in biomedical fields are suitable for the registration of GB-scale data volumes. For example, in one study 21 registering a 12.5 μm 3 resolution whole-brain dataset approximate to 1 GB. Thebrain 9 import outline registration#Ĭlearly, the nonlinear registration algorithm is a global optimization solution that consumes large amounts of memory 22. Thus, the strategy of obtaining the transformation parameters at low resolution and warping massive amounts of data in blocks is a better choice. ![]() Thebrain 9 import outline registration#Ģ3 developed a block-based fast warping tool that successfully aligned several GB-volume datasets.
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