Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy.

Area of Science:

• Neuroimaging
• Computational Neuroscience
• Medical Image Analysis

Background:

• Traditional brain mapping relies on
• iconic
• approaches using dense deformation fields.
• These methods assume continuous mapping, which is not always valid, limiting the study of structures with high variability.
• Cortical sulci, in particular, exhibit significant variations in size, shape, and topology, making iconic approaches inefficient.

Purpose of the Study:

• To present a complementary
• structural
• approach for brain mapping.
• To introduce Anatomist, a 3D visualization software for building, exploring, and editing structural atlases.
• To address the limitations of iconic methods in studying variable brain structures like cortical sulci.

Main Methods:

• Developed a
• structural
• atlas approach, extracting and comparing individual brain structures without deformation.
• Utilized Anatomist software for building and visualizing structural atlases from multiple subjects.
• Trained sulci identification algorithms using these structural atlases.

Main Results:

• Demonstrated the effectiveness of the structural atlas approach for characterizing brain structure variability.
• Anatomist software supports multimodal, multi-individual, and inter-species data visualization.
• The software handles complex neuroimaging data, including structural object graphs and arbitrary transformations.

Conclusions:

• The structural atlas approach offers a powerful alternative to iconic methods for brain mapping, especially for highly variable structures.
• Anatomist is a versatile tool for building and exploring structural atlases, applicable to various neuroimaging data and research questions.
• The software's generic design allows for extension and integration into other applications for diverse neuroanatomical studies.