Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation

Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation

Abstract The application of deep learning techniques for the analysis of neuroimaging has been increasing recently. The 3D Convolutional Neural Network (CNN) technology, which is commonly adopted to encode volumetric information, requires a large number of datasets. However, due to the nature of the...

Full description

Saved in:
Bibliographic Details
Main Authors: Hyemin Yoon, Do-Young Kang, Sangjin Kim
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Parkinson’s disease
Dopamine transporter
SPECT
Functional neuroimaging
Deep learning
Knowledge distillation
Online Access:https://doi.org/10.1038/s41598-024-80938-6
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-024-80938-6

Similar Items