MRI-based Alzheimer's disease prediction via distilling the knowledge in multi-modal data

04/08/2021
by   Hao Guan, et al.
0

Mild cognitive impairment (MCI) conversion prediction, i.e., identifying MCI patients of high risks converting to Alzheimer's disease (AD), is essential for preventing or slowing the progression of AD. Although previous studies have shown that the fusion of multi-modal data can effectively improve the prediction accuracy, their applications are largely restricted by the limited availability or high cost of multi-modal data. Building an effective prediction model using only magnetic resonance imaging (MRI) remains a challenging research topic. In this work, we propose a multi-modal multi-instance distillation scheme, which aims to distill the knowledge learned from multi-modal data to an MRI-based network for MCI conversion prediction. In contrast to existing distillation algorithms, the proposed multi-instance probabilities demonstrate a superior capability of representing the complicated atrophy distributions, and can guide the MRI-based network to better explore the input MRI. To our best knowledge, this is the first study that attempts to improve an MRI-based prediction model by leveraging extra supervision distilled from multi-modal information. Experiments demonstrate the advantage of our framework, suggesting its potentials in the data-limited clinical settings.

READ FULL TEXT

page 2

page 9

page 10

page 17

page 18

page 19

research
07/14/2023

TriFormer: A Multi-modal Transformer Framework For Mild Cognitive Impairment Conversion Prediction

The prediction of mild cognitive impairment (MCI) conversion to Alzheime...
research
07/05/2022

Is a PET all you need? A multi-modal study for Alzheimer's disease using 3D CNNs

Alzheimer's Disease (AD) is the most common form of dementia and often d...
research
07/19/2021

Input Agnostic Deep Learning for Alzheimer's Disease Classification Using Multimodal MRI Images

Alzheimer's disease (AD) is a progressive brain disorder that causes mem...
research
12/24/2018

Self-Attention Equipped Graph Convolutions for Disease Prediction

Multi-modal data comprising imaging (MRI, fMRI, PET, etc.) and non-imagi...
research
03/22/2023

MEDIMP: Medical Images and Prompts for renal transplant representation learning

Renal transplantation emerges as the most effective solution for end-sta...
research
07/03/2023

End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformers

Knee Osteoarthritis (KOA) is a highly prevalent chronic musculoskeletal ...
research
11/19/2018

IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet

Accurate localization and segmentation of intervertebral disc (IVD) is c...

Please sign up or login with your details

Forgot password? Click here to reset