BL

Bo Li

9 records found

Evaluating the sustainable development level and obstacle factors of small towns is an important guarantee for implementing China's new-type urbanization and rural revitalization strategies, and is also a key path to promoting the United Nations Sustainable Development Goal 11 (S ...
Exploring the influence of settlement patterns on the landscape fragmentation in woodlands and biological reserves is key to achieving ecologically sustainable development. In this research, we chose the Nanshan National Park in Hunan Province, China, as a case study, to explore ...
Outdoor physical activities can promote public health and they are largely influenced by the built environment in different urban settings. Understanding the association between outdoor physical activities and the built environment is important for promoting a high quality of lif ...
Using short-wave infrared wavelength advantages, we demonstrate one-photon fluorescence confocal microscopy of adult mouse brains with penetration depths up to 1.7mm. This is achieved by labeling quantum dots with 1300 nm excitation and 1700 nm emission and detecting them with a ...
With the advancement of urbanization, the stress on the green infrastructure around the urban agglomeration has intensified, which causes severe ecological problems. The uncertainty of urban growth makes it difficult to achieve effective protection only by setting protection red ...
Optical microscopy is a valuable tool for in vivo monitoring of biological structures and functions because of its noninvasiveness. However, imaging deep into biological tissues is challenging due to the scattering and absorption of light. Previous research has shown that the two ...
Analysis of longitudinal changes in imaging studies often involves both segmentation of structures of interest and registration of multiple timeframes. The accuracy of such analysis could benefit from a tailored framework that jointly optimizes both tasks to fully exploit the inf ...

Longitudinal diffusion MRI analysis using Segis-Net

A single-step deep-learning framework for simultaneous segmentation and registration

This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and reg ...
Confounding bias is a crucial problem when applying machine learning to practice, especially in clinical practice. We consider the problem of learning representations independent to multiple biases. In literature, this is mostly solved by purging the bias information from learned ...