54 research outputs found
RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation
Medical image segmentation methods are generally designed as fully-supervised
to guarantee model performance, which require a significant amount of expert
annotated samples that are high-cost and laborious. Semi-supervised image
segmentation can alleviate the problem by utilizing a large number of unlabeled
images along with limited labeled images. However, learning a robust
representation from numerous unlabeled images remains challenging due to
potential noise in pseudo labels and insufficient class separability in feature
space, which undermines the performance of current semi-supervised segmentation
approaches. To address the issues above, we propose a novel semi-supervised
segmentation method named as Rectified Contrastive Pseudo Supervision (RCPS),
which combines a rectified pseudo supervision and voxel-level contrastive
learning to improve the effectiveness of semi-supervised segmentation.
Particularly, we design a novel rectification strategy for the pseudo
supervision method based on uncertainty estimation and consistency
regularization to reduce the noise influence in pseudo labels. Furthermore, we
introduce a bidirectional voxel contrastive loss to the network to ensure
intra-class consistency and inter-class contrast in feature space, which
increases class separability in the segmentation. The proposed RCPS
segmentation method has been validated on two public datasets and an in-house
clinical dataset. Experimental results reveal that the proposed method yields
better segmentation performance compared with the state-of-the-art methods in
semi-supervised medical image segmentation. The source code is available at
https://github.com/hsiangyuzhao/RCPS
Association between radiomics features of DCE-MRI and CD8+ and CD4+ TILs in advanced gastric cancer
Objective: The aim of this investigation was to explore the correlation between the levels of tumor-infiltrating CD8+ and CD4+ T cells and the quantitative pharmacokinetic parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with advanced gastric cancer.Methods: We retrospectively analyzed the data of 103 patients with histopathologically confirmed advanced gastric cancer (AGC). Three pharmacokinetic parameters, Kep, Ktrans, and Ve, and their radiomics characteristics were obtained by Omni Kinetics software. Immunohistochemical staining was used to determine CD4+ and CD8+ TILs. Statistical analysis was subsequently performed to assess the correlation between radiomics characteristics and CD4+ and CD8+ TIL density.Results: All patients included in this study were finally divided into either a CD8+ TILs low-density group (n = 51) (CD8+ TILs < 138) or a high-density group (n = 52) (CD8+ TILs ≥ 138), and a CD4+ TILs low-density group (n = 51) (CD4+ TILs < 87) or a high-density group (n = 52) (CD4+ TILs ≥ 87). ClusterShade and Skewness based on Kep and Skewness based on Ktrans both showed moderate negative correlation with CD8+ TIL levels (r = 0.630–0.349, p < 0.001), with ClusterShade based on Kep having the highest negative correlation (r = −0.630, p < 0.001). Inertia-based Kep showed a moderate positive correlation with the CD4+ TIL level (r = 0.549, p < 0.001), and the Correlation based on Kep showed a moderate negative correlation with the CD4+ TIL level, which also had the highest correlation coefficient (r = −0.616, p < 0.001). The diagnostic efficacy of the above features was assessed by ROC curves. For CD8+ TILs, ClusterShade of Kep had the highest mean area under the curve (AUC) (0.863). For CD4+ TILs, the Correlation of Kep had the highest mean AUC (0.856).Conclusion: The radiomics features of DCE-MRI are associated with the expression of tumor-infiltrating CD8+ and CD4+ T cells in AGC, which have the potential to noninvasively evaluate the expression of CD8+ and CD4+ TILs in AGC patients
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images
Cross-modality synthesis (CMS), super-resolution (SR), and their combination
(CMSR) have been extensively studied for magnetic resonance imaging (MRI).
Their primary goals are to enhance the imaging quality by synthesizing the
desired modality and reducing the slice thickness. Despite the promising
synthetic results, these techniques are often tailored to specific tasks,
thereby limiting their adaptability to complex clinical scenarios. Therefore,
it is crucial to build a unified network that can handle various image
synthesis tasks with arbitrary requirements of modality and resolution
settings, so that the resources for training and deploying the models can be
greatly reduced. However, none of the previous works is capable of performing
CMS, SR, and CMSR using a unified network. Moreover, these MRI reconstruction
methods often treat alias frequencies improperly, resulting in suboptimal
detail restoration. In this paper, we propose a Unified Co-Modulated Alias-free
framework (Uni-COAL) to accomplish the aforementioned tasks with a single
network. The co-modulation design of the image-conditioned and stochastic
attribute representations ensures the consistency between CMS and SR, while
simultaneously accommodating arbitrary combinations of input/output modalities
and thickness. The generator of Uni-COAL is also designed to be alias-free
based on the Shannon-Nyquist signal processing framework, ensuring effective
suppression of alias frequencies. Additionally, we leverage the semantic prior
of Segment Anything Model (SAM) to guide Uni-COAL, ensuring a more authentic
preservation of anatomical structures during synthesis. Experiments on three
datasets demonstrate that Uni-COAL outperforms the alternatives in CMS, SR, and
CMSR tasks for MR images, which highlights its generalizability to wide-range
applications
Retinoic acid deficiency alters second heart field formation
Retinoic acid (RA), the active derivative of vitamin A, has been implicated in various steps of cardiovascular development. The retinaldehyde dehydrogenase 2 (RALDH2) enzyme catalyzes the second oxidative step in RA biosynthesis and its loss of function creates a severe embryonic RA deficiency. Raldh2(−/−) knockout embryos fail to undergo heart looping and have impaired atrial and sinus venosus development. To understand the mechanism(s) producing these changes, we examined the contribution of the second heart field (SHF) to pharyngeal mesoderm, atria, and outflow tract in Raldh2(−/−) embryos. RA deficiency alters SHF gene expression in two ways. First, Raldh2(−/−) embryos exhibited a posterior expansion of anterior markers of the SHF, including Tbx1, Fgf8, and the Mlc1v-nlacZ-24/Fgf10 reporter transgene as well as of Islet1. This occurred at early somite stages, when cardiac defects became irreversible in an avian vitamin A-deficiency model, indicating that endogenous RA is required to restrict the SHF posteriorly. Explant studies showed that this expanded progenitor population cannot differentiate properly. Second, RA up-regulated cardiac Bmp expression levels at the looping stage. The contribution of the SHF to both inflow and outflow poles was perturbed under RA deficiency, creating a disorganization of the heart tube. We also investigated genetic cross-talk between Nkx2.5 and RA signaling by generating double mutant mice. Strikingly, Nkx2.5 deficiency was able to rescue molecular defects in the posterior region of the Raldh2(−/−) mutant heart, in a gene dosage-dependent manner
A Questionnaire Survey on the Sense of Educational and Social Equities among College Students in China
The sense of equity reflects how fair a domain is as evaluated by those engaging in that domain. It is very meaningful to explore the sense of equity among college students, which are a special group of people. This study carried out a questionnaire survey on the sense of equity among 982 college students in China, from the perspectives of educational equity and social equity. The questions were validated by the 27/73 quantile method, and the survey results were analyzed through one-way analysis of variance (one-way ANOVA). The results showed that the college students could evaluate the sense of equity rather accurately and generally had a higher sense of equity, but failed to sense the social outcome equity well; their sense of social equity was lower than the sense of educational equity; the sense of equity varied between college students in different majors: the science majors had a lower sense of equity than those majoring in liberal arts; some college students had a misunderstanding of equity
The Dominant Driving Force of Forest Change in the Yangtze River Basin, China: Climate Variation or Anthropogenic Activities?
Under the combined effect of climate variations and anthropogenic activities, the forest ecosystem in the Yangtze River Basin (YRB) has experienced dramatic changes in recent decades. Quantifying their relative contributions can provide a valuable reference for forest management and ecological sustainability. In this study, we selected net primary productivity (NPP) as an indicator to investigate forest variations. Meanwhile, we established eight scenarios based on the slope coefficients of the potential NPP (PNPP) and actual NPP (ANPP), and human-induced NPP (HNPP) to quantify the contributions of anthropogenic activities and climate variations to forest variations in the YRB from 2000 to 2015. The results revealed that in general, the total forest ANPP increased by 10.42 TgC in the YRB, and forest restoration occurred in 57.25% of the study area during the study period. The forest degradation was mainly observed in the Wujiang River basin, Dongting Lake basin, and Poyang Lake basin. On the whole, the contribution of anthropogenic activities was greater than climate variations on both forest restoration and degradation in the YRB. Their contribution to forest restoration and degradation varied in different tributaries. Among the five forest types, shrubs experienced the most severe degradation during the study period, which should arouse great attention. Ecological restoration programs implemented in YRB have effectively mitigated the adverse effect of climate variations and dominated forest restoration, while rapid urbanization in the mid-lower region has resulted in forest degradation. The forest degradation in Dongting Lake basin and Poyang Lake basin may be ascribed to the absence of the Natural Forest Conservation Program. Therefore, we recommend that the extent of the Natural Forest Conservation Program should expand to cover these two basins. The current research could improve the understanding of the driving mechanism of forest dynamics and promote the effectiveness of ecological restoration programs in the YRB
The Dominant Driving Force of Forest Change in the Yangtze River Basin, China: Climate Variation or Anthropogenic Activities?
Under the combined effect of climate variations and anthropogenic activities, the forest ecosystem in the Yangtze River Basin (YRB) has experienced dramatic changes in recent decades. Quantifying their relative contributions can provide a valuable reference for forest management and ecological sustainability. In this study, we selected net primary productivity (NPP) as an indicator to investigate forest variations. Meanwhile, we established eight scenarios based on the slope coefficients of the potential NPP (PNPP) and actual NPP (ANPP), and human-induced NPP (HNPP) to quantify the contributions of anthropogenic activities and climate variations to forest variations in the YRB from 2000 to 2015. The results revealed that in general, the total forest ANPP increased by 10.42 TgC in the YRB, and forest restoration occurred in 57.25% of the study area during the study period. The forest degradation was mainly observed in the Wujiang River basin, Dongting Lake basin, and Poyang Lake basin. On the whole, the contribution of anthropogenic activities was greater than climate variations on both forest restoration and degradation in the YRB. Their contribution to forest restoration and degradation varied in different tributaries. Among the five forest types, shrubs experienced the most severe degradation during the study period, which should arouse great attention. Ecological restoration programs implemented in YRB have effectively mitigated the adverse effect of climate variations and dominated forest restoration, while rapid urbanization in the mid-lower region has resulted in forest degradation. The forest degradation in Dongting Lake basin and Poyang Lake basin may be ascribed to the absence of the Natural Forest Conservation Program. Therefore, we recommend that the extent of the Natural Forest Conservation Program should expand to cover these two basins. The current research could improve the understanding of the driving mechanism of forest dynamics and promote the effectiveness of ecological restoration programs in the YRB
Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China
Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions
Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China
Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions
- …