Fijiyama

Fijiyama registers and aligns three-dimensional (3D) image series from MRI, X-ray CT, microscopy, and photography to enable integration of multimodal and time-lapse imaging data.

Key Features:

• Versatility across modalities: Handles MRI, X-ray CT, microscopy, and photography for construction of multimodal datasets.
• Automated 3D alignment: Automates alignment of 3D images acquired at successive time points or by different imaging systems.
• Multimodal integration: Combines outputs from multiple imaging sources into cohesive datasets for comparative analysis.
• Identification of image invariants: Identifies image invariants across modalities to support registration despite variability in imaging outputs.
• Use of established registration algorithms: Builds upon established biomedical registration algorithms to achieve accurate alignment of multimodal and time-lapse data.

Scientific Applications:

• Non-destructive time-lapse imaging: Enables longitudinal experiments that observe anatomy, structure, and function of tissues over time without destructive sampling.
• Longitudinal multiscale studies: Supports longitudinal studies across micro to macro scales by aligning serial 3D image series.
• Multimodal comparative analysis: Facilitates integration of MRI, X-ray CT, microscopy, and photographic data for comparative and correlative imaging analyses.

Methodology:

Identifies image invariants across modalities and applies established biomedical registration algorithms to register and align 3D image series from MRI, X-ray CT, microscopy, and photography.