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SUMMARY:Illuminating the Void: Data-Consistent Diffusion Reconstruction fo
 r Brain Imaging in X-Ray Laminography
DTSTART:20260917T093000Z
DTEND:20260917T110000Z
DTSTAMP:20260920T152900Z
UID:indico-event-19353@indico.psi.ch
CONTACT:benjamin.bejar@psi.ch
DESCRIPTION:Speakers: Wenxuan Fang\n\nAbstract:\nMapping neural circuits r
 equires three-dimensional imaging at nanometer resolution across large vol
 umes of brain tissue. X-ray laminography is a promising approach for imagi
 ng extended biological specimens\, but its acquisition geometry leaves par
 t of Fourier space unmeasured\, creating a severe missing-cone problem tha
 t degrades reconstruction quality.\nIn this talk\, I will introduce LUCID\
 , a data-consistent reconstruction framework that combines multi-view diff
 usion priors with the physical forward model of X-ray laminography. By alt
 ernating between generative inference and measurement-consistency updates\
 , LUCID recovers missing structural information while remaining faithful t
 o the acquired data.\nI will provide an intuitive introduction to tomograp
 hy\, laminography\, and diffusion models for inverse problems\, and demons
 trate how the integration of physics and AI enables high-fidelity reconstr
 uction of brain tissue from incomplete measurements.\nTEAMS link \n\nhttps
 ://indico.psi.ch/event/19353/
LOCATION:OHSA/B17
URL:https://indico.psi.ch/event/19353/
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