# Fast and robust deep learning tools for analysis of neuroimaging data of Alzheimer's disease

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2024 · $699,850

## Abstract

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder. Interventions at the preclinical
and prodromal stages are appealing targets for slowing or halting disease progression. It is desired to
achieve accurate prognosis of AD dementia and cognitive decline for people with mild cognitive impairment
who have increased risk to develop AD. In order to achieve fast and accurate prognosis of AD dementia
based on neuroimaging data, we will develop and validate novel deep learning techniques. Particularly, we
will develop unsupervised deep learning methods for segmenting brain images and reconstructing cortical
surfaces from structural magnetic resonance imaging data. These fast and accurate image processing
methods will be used in conjunction with advanced deep learning methods to build prognosis models of AD
dementia and cognitive decline in a time-to-event analysis framework using large-scale imaging datasets.
Finally, we will develop and disseminate a user friendly, open source, modular, and extensible software
package to improve prognosis of AD dementia. Source code, standalone programs, and web-application
interfaces of all the algorithms will be made available on GitHub and NITRC. Our tools will enable real-time
neuroimaging data analysis and can find applications in diverse fields, including quantifying brain changes
associated with aging and development.

## Key facts

- **NIH application ID:** 10799585
- **Project number:** 5R01AG066650-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Yong Fan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $699,850
- **Award type:** 5
- **Project period:** 2021-03-15 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10799585

## Citation

> US National Institutes of Health, RePORTER application 10799585, Fast and robust deep learning tools for analysis of neuroimaging data of Alzheimer's disease (5R01AG066650-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10799585. Licensed CC0.

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