Leland Stanford Junior University

Jennifer McNab

Christoph Leuze

Karl A Deisseroth

Li Ye

Supriya Sathyanarayana

Qiyuan Tian

Improved targeting of cranial therapy is provided by warping a general purpose brain atlas to a measured head shape of the patient. The resulting patient-specific transformation from brain atlas to patient's head allows one to estimate the location of brain features of the patient without any patient specific brain imaging. Such cost-effective targeting of brain features is especially useful for therapies like transcranial magnetic stimulation, where accuracy of targeting brain structures and session-to-session consistency are both important.

Accurate patient-specific targeting of cranial therapy using a brain atlas

3D alignment of a virtual model and corresponding real-world object is provided. A user places virtual tags on the real-world object as viewed through an augmented reality device. By placing these tags at the positions where he perceives certain real-world landmark locations, this allows for correction of misalignments between virtual content on the AR display and the real world. In particular, the virtual model include virtual landmarks that correspond to the real-world landmarks. Thus aligning the virtual landmarks of the virtual model to the virtual tags provides accurate alignment of the virtual model to the corresponding real-world object.

3D-perceptually accurate manual alignment of virtual content with the real world with an augmented reality device

Aspects of the present disclosure include a method for visualizing a fiber-like structure in a biological specimen, the method comprising: clearing the biological specimen comprising a fiber-like structure, wherein the fiber-like structure is detectably labeled; illuminating the cleared biological specimen with two light sheets from a first side and a second side to produce an image volume, wherein the second side is opposite to the first side and wherein the image volume comprises a representation of the fiber-like structure; defining a plurality of voxels within the representation of the fiber-like structure; processing each of the plurality of voxels to estimate a plurality of principal fiber-like structure orientations; and defining a starting point on the representation of the fiber-like structure and propagating a plurality of streamlines from the starting point, according to the plurality of principal fiber-like structure.

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Stanford, CA, United States of America

Jennifer McNab