# Statistical models for the integrative analysis of complex biomedical images with manifold structure

> **NIH NIH R03** · UNIVERSITY OF WASHINGTON · 2024 · $75,407

## Abstract

PROJECT SUMMARY
Modern multimodal biomedical imaging data have the potential to advance our ability to diagnose
medical conditions and to understand the biological mechanisms underlying disease progression.
However, these data typically display non-linear geometric structure, i.e., manifold structure, which
limits the applicability of classical statistical methods to gain further knowledge from the analysis of
the contemporary biomedical datasets. This project will focus on the development of novel
statistical methods for the analysis of biomedical images with manifold structure that are subject-
specific anatomical objects coupled with ‘signals' that are structural or functional images. Examples
of such data are fMRI signals, seed-based connectivity maps, or cortical thickness measurements
located on the highly convoluted subject-specific cortical surfaces. The proposed methods will
model these data as ‘functional data', i.e., without relying on oversimplified representations that
could lead to the loss of relevant biological information. In practice, the proposed framework will
allow researchers to relate anatomical, structural, and functional imaging features to other
variables typically collected, such as disease status, treatment type, or genetic information, with
the aim of validating scientific hypotheses or discovering novel imaging biomarkers. The models
developed will be made available as free and open-source tools that can easily interface with the
most popular data analysis software for them to become part of the larger imaging software
ecosystem.

## Key facts

- **NIH application ID:** 10796918
- **Project number:** 5R03EB033001-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Eardi Lila
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $75,407
- **Award type:** 5
- **Project period:** 2023-03-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10796918

## Citation

> US National Institutes of Health, RePORTER application 10796918, Statistical models for the integrative analysis of complex biomedical images with manifold structure (5R03EB033001-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10796918. Licensed CC0.

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