5 research outputs found
Region Refinement Network for Salient Object Detection
Albeit intensively studied, false prediction and unclear boundaries are still
major issues of salient object detection. In this paper, we propose a Region
Refinement Network (RRN), which recurrently filters redundant information and
explicitly models boundary information for saliency detection. Different from
existing refinement methods, we propose a Region Refinement Module (RRM) that
optimizes salient region prediction by incorporating supervised attention masks
in the intermediate refinement stages. The module only brings a minor increase
in model size and yet significantly reduces false predictions from the
background. To further refine boundary areas, we propose a Boundary Refinement
Loss (BRL) that adds extra supervision for better distinguishing foreground
from background. BRL is parameter free and easy to train. We further observe
that BRL helps retain the integrity in prediction by refining the boundary.
Extensive experiments on saliency detection datasets show that our refinement
module and loss bring significant improvement to the baseline and can be easily
applied to different frameworks. We also demonstrate that our proposed model
generalizes well to portrait segmentation and shadow detection tasks
Comparison and evaluation of two different methods to establish the cigarette smoke exposure mouse model of COPD
Animal model of cigarette smoke (CS) -induced chronic obstructive pulmonary disease (COPD) is the primary testing methodology for drug therapies and studies on pathogenic mechanisms of disease. However, researchers have rarely run simultaneous or side-by-side tests of whole-body and nose-only CS exposure in building their mouse models of COPD. We compared and evaluated these two different methods of CS exposure, plus airway Lipopolysaccharides (LPS) inhalation, in building our COPD mouse model. Compared with the control group, CS exposed mice showed significant increased inspiratory resistance, functional residual capacity, right ventricular hypertrophy index, and total cell count in BALF. Moreover, histological staining exhibited goblet cell hyperplasia, lung inflammation, thickening of smooth muscle layer on bronchia, and lung angiogenesis in both methods of CS exposure. Our data indicated that a viable mouse model of COPD can be established by combining the results from wholebody CS exposure, nose-only CS exposure, and airway LPS inhalation testing. However, in our study, we also found that, given the same amount of particulate intake, changes in right ventricular pressure and intimal thickening of pulmonary small artery are a little more serious in nose-only CS exposure method than changes in the whole-body CS exposure method.National Natural Science Foundation of China [81630004, 81470246, 81220108001, 81520108001]; Guangdong Department of Science and Technology of China [2016A030311020, 2016A030313606]; Guangzhou Department of Education Yangcheng Scholarship [12A001S]; Guangzhou Department of Education Scholarship [1201630095]; Guangzhou Department of Science and Technology [2014Y2-00167, 201607010358]; Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme, ChinaThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]