17 research outputs found
Software for Whole Cervix Diffusion Basis Spectrum Imaging of Collagen, Muscle, and Cellularity
No full text<p>The zip folder contains two subfolders:</p>
<ol>
<li>Installer_wMatlabRuntimeEngine: for installing whole cervix DBSI executable with MATLAB 2022b runtime engine.</li>
<li>Binary: whole cervix DBSI executable (contains readme.txt, test dataset)</li>
</ol>
<p>Input: </p>
<ol>
<li>4D DWI data in NIfTI format</li>
<li>b table in .mat</li>
<li>Segmenation mask in NIfTI format</li>
<li>Flag to select 'exvivo' or 'invivo'</li>
</ol>
<p>Output in NIfTI format: </p>
<ol>
<li>DBSI cell ratio map</li>
<li>DBSI collagen ratio map</li>
<li>DBSI muscle ratio map</li>
<li>DBSI water ratio map</li>
</ol>
<p> </p>
<p>Please don't hesitate to reach out to Dr. Yong Wang ([email protected]), the principal investigator of this project, to request access to the software.</p>
Advanced Diffusion MRI Technique and Applications in Placenta and Brain
No full textAmong a series of contrasts of MRI, diffusion MRI (dMRI) is different from conventional MRI by its ability to capture information about the random movement of water molecules and their interaction with local tissue microstructures. This capability holds the potential to reveal intricate subvoxel microstructural information linked to pathological changes, offering potential imaging biomarkers. A higher-order diffusion analysis model helps to yield more accurate and specific parameters but requires more extensive parameter tuning and higher image quality. In this study, we firstly fine-tuned the previously developed diffusion basis spectrum imaging (DBSI) method to strike a balance between efficiency and accuracy when dealing with various b-table designs, signal-to-noise ratios (SNR), and organ-of-interest (Chapter 2). The dMRI data, usually obtained through echoplanar imaging (EPI), frequently encounter challenges related to misalignment of the image caused by the motion of the subject. This is- sue is particularly pronounced in placenta imaging, where fetal movements are unpredictable and uncontrollable. To address this issue, we devised a tailored registration pipeline capable of mitigating both intra-volume and inter-volume misalignment (Chapter 3). Furthermore, we noticed the absence of detailed segmentation methods within placenta re- gion, as most of the previous study used the average value from either the entire placenta or several manually labelled regions. We developed an automatic separation method con- sidering dMRI and T2* MRI features that divides placenta into subregions. The improved more specific compartment-wise quantification revealed new insights in longitudinal changes in placenta (Chapter 4). In the DBSI placenta application, we carefully performed ex vivo validation and simulation validation before in-vivo application. The method imaged the spatial distribution of the placental immune cells and revealed significantly greater immune cell infiltration in the in- flammation placentas throughout gestation, demonstrating its potential to serve as a clinical tool to monitor the placenta immune status of pregnancy longitudinally without ionizing radiation (Chapter 5). Finally, although DBSI was initially developed and validated in brain studies, we recently recognized its potential for enhancement, inspired by an in vivo observation of increasing cell ADC along progress of Alzheimer’s disease (AD). We targeted microglia as a potential marker and hypothesized that DBSI can quantify the proliferation and activation of microglia with Monte-Carlo simulated reference signal from real microglia model (Chapter 6)
A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain
No full textAbstract Recently, imaging investigation of brain development has increasingly captured the attention of researchers and clinicians in an attempt to understand the link between the brain and behavioral changes. Although high-field MR imaging of infants is feasible, the necessary customizations have limited its accessibility, affordability, and reproducibility. Low-field MR, as an emerging solution for scrutinizing developing brain, has exhibited its unique advantages in safety, portability, and cost-effectiveness. The presented low-field infant structural MR data aims to manifest the feasibility of using low-field MR image to exam brain structural changes during early life in infants. The dataset comprises 100 T2 weighed MR images from infants with in-plane resolution of ~0.85 mm and ~6 mm slice thickness. To demonstrate the potential utility, we conducted atlas-based whole brain segmentations and volumetric quantifications to analyze brain development features in first 10 week in postnatal life. This dataset addresses the scarcity of a large, extended-span infant brain dataset that restricts the further tracking of infant brain development trajectories and the development of routine low-field MR imaging pipelines
The protective effects of Lipoxin A(4) during the early phase of severe acute pancreatitis in rats
No full textObjective. Our aim was to investigate the protective effects of a Lipoxin A(4) analogue (LXA(4)) in the early phase of acute pancreatitis in rats. Materials and methods. Severe acute pancreatitis (SAP) was induced by injection of 5% sodium taurocholate into the pancreatic duct. Rats with SAP were treated with LXA(4) (0.1 mg/kg), 10 min after the 5% sodium taurocholate injection, after which LXA(4) was administrated every 8 hours, three times (LXA(4) group). The sham group was only given the vehicle after operation. Plasma amylase activity, serum levels of interleukin-1 (IL-1), IL-6, and tumor necrosis factor-alpha (TNF-alpha) were measured at 4, 12, and 24 h after induction of SAP. The pancreatic index and histopathologic observations were evaluated and the expression of intercellular adhesion molecule-1 (ICAM-1) and NF-kappa B p65 in the pancreas, and the expression of ICAM-1 in the lungs were detected by immunohistochemistry. Results. LXA(4) treated rats had lower serum levels of TNF-alpha, IL-1, and IL-6 at all time points measured (p < 0.05), but significantly differed in plasma amylase activity only at 24 h as compared with the SAP group. The pancreatic index and the scores of pancreatitic histopathologic evaluations were lower in the LXA(4) group as compared to the SAP group. Immunohistochemistry showed that LXA(4) attenuated the expression of ICAM-1 and NF-kappa B p65 in the pancreas, as well as the expression of ICAM-1 in the lungs in animals with pancreatitis (p < 0.05). Conclusions. We demonstrate that LXA(4) has protective effects in experimental SAP, which may be achieved by inhibiting the NF-kappa B signalling pathway, thereby reducing the production of proinflammatory cytokines
3D bi-directional transformer U-Net for medical image segmentation
No full textAs one of the popular deep learning methods, deep convolutional neural networks (DCNNs) have been widely adopted in segmentation tasks and have received positive feedback. However, in segmentation tasks, DCNN-based frameworks are known for their incompetence in dealing with global relations within imaging features. Although several techniques have been proposed to enhance the global reasoning of DCNN, these models are either not able to gain satisfying performances compared with traditional fully-convolutional structures or not capable of utilizing the basic advantages of CNN-based networks (namely the ability of local reasoning). In this study, compared with current attempts to combine FCNs and global reasoning methods, we fully extracted the ability of self-attention by designing a novel attention mechanism for 3D computation and proposed a new segmentation framework (named 3DTU) for three-dimensional medical image segmentation tasks. This new framework processes images in an end-to-end manner and executes 3D computation on both the encoder side (which contains a 3D transformer) and the decoder side (which is based on a 3D DCNN). We tested our framework on two independent datasets that consist of 3D MRI and CT images. Experimental results clearly demonstrate that our method outperforms several state-of-the-art segmentation methods in various metrics
3D bi-directional transformer U-Net for medical image segmentation
No full textAs one of the popular deep learning methods, deep convolutional neural networks (DCNNs) have been widely adopted in segmentation tasks and have received positive feedback. However, in segmentation tasks, DCNN-based frameworks are known for their incompetence in dealing with global relations within imaging features. Although several techniques have been proposed to enhance the global reasoning of DCNN, these models are either not able to gain satisfying performances compared with traditional fully-convolutional structures or not capable of utilizing the basic advantages of CNN-based networks (namely the ability of local reasoning). In this study, compared with current attempts to combine FCNs and global reasoning methods, we fully extracted the ability of self-attention by designing a novel attention mechanism for 3D computation and proposed a new segmentation framework (named 3DTU) for three-dimensional medical image segmentation tasks. This new framework processes images in an end-to-end manner and executes 3D computation on both the encoder side (which contains a 3D transformer) and the decoder side (which is based on a 3D DCNN). We tested our framework on two independent datasets that consist of 3D MRI and CT images. Experimental results clearly demonstrate that our method outperforms several state-of-the-art segmentation methods in various metrics
Exogenous cAMP upregulates the expression of glnII and glnK-amtB genes in Sinorhizobium meliloti 1021
No full textTian ZX, Mao X, Su W, Li J, Becker A, Wang Y. Exogenous cAMP upregulates the expression of glnII and glnK-amtB genes in Sinorhizobium meliloti 1021. CHINESE SCIENCE BULLETIN. 2006;51(16):1982-1985.The existence of multiple adenylate cyclase encoding genes implies the importance of cAMP in Sinorhizobium meliloti 1021. In this study, as a pioneer step of understanding CAMP roles, microarray analysis on S. meliloti was carried out for the function of exogenous CAMP. To our surprise, the result showed that the transcriptions of gInII and gInK genes were significantly upshifted in the presence of exogenous CAMP in S. meliloti. This phenomenon is further confirmed in S. meliloti that the expression of either glnll or gInK promoter-lacZ translational fusion is higher in the presence of exogenous cAMP. Therefore, for the first time, we have identified genes from S. meliloti whose expression is activated by CAMP. The potential physiological role of upregulation of glnll and g1nK by cAMP is discussed
Analysis of Electrophysiological Activation of the Uterus During Human Labor Contractions
No full textThis cohort study uses electromyometrial imaging to examine the underlying electrophysiological origins of human labor at the myometrium level
A dataset for quality evaluation of pelvic X-ray and diagnosis of developmental dysplasia of the hip
No full textAbstract Developmental Dysplasia of the Hip (DDH) stands as one of the preeminent hip disorders prevalent in pediatric orthopedics. Automated diagnostic instruments, driven by artificial intelligence methodologies, are capable of providing substantial assistance to clinicians in the diagnosis of DDH. We have developed a dataset designated as Multitasking DDH (MTDDH), which is composed of two sub-datasets. Dataset 1 encompasses 1,250 pelvic X-ray images, with annotations demarcating four discrete regions for the evaluation of pelvic X-ray quality, in tandem with eight pivotal points serving as support for DDH diagnosis. Dataset 2 contains 906 pelvic X-ray images, and each image has been annotated with eight key points for assisting in the diagnosis of DDH. Notably, MTDDH represents the pioneering dataset engineered for the comprehensive evaluation of pelvic X-ray quality while concurrently offering the most exhaustive set of eight key points to bolster DDH diagnosis, thus fulfilling the exigency for enhanced diagnostic precision. Ultimately, we presented the elaborate process of constructing the MTDDH and furnished a concise introduction regarding its application
