A deep learning classification task for brain navigation in rodents using micro-Doppler ultrasound imaging.

ABSTRACT: Positioning and navigation are essential components of neuroimaging as they improve the quality and reliability of data acquisition, leading to advances in diagnosis, treatment outcomes, and fundamental understanding of the brain. Functional ultrasound imaging is an emerging technology providing high-resolution images of the brain vasculature, allowing for the monitoring of brain activity. However, as the technology is relatively new, there is no standardized tool for inferring the position in the brain from the vascular images. In this study, we present a deep learning-based framework designed to address this challenge. Our approach uses an image classification task coupled with a regression on the resulting probabilities to determine the position of a single image. To evaluate its perfor

SUBMITTER: Lambert T 

PROVIDER: S-EPMC10943389 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature