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- 저자 : Li Fangfei (검색결과 3 건)
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Gyral net: A new representation of cortical folding organization
Chen, Hanbo,Li, Yujie,Ge, Fangfei,Li, Gang,Shen, Dinggang,Liu, Tianming Elsevier 2017 Medical image analysis Vol.42 No.-
<P><B>Abstract</B></P> <P>One distinct feature of the cerebral cortex is its convex (gyri) and concave (sulci) folding patterns. Due to the remarkable complexity and variability of gyral/sulcal shapes, it has been challenging to quantitatively model their organization patterns. Inspired by the observation that the lines of gyral crests can form a connected graph on each brain hemisphere, we propose a new representation of cortical gyri/sulci organization pattern – gyral net, which models cortical architecture from a graph perspective, starting with nodes and edges obtained from the reconstructed cortical surfaces. A novel computational framework is developed to efficiently and automatically construct gyral nets from surface meshes, and four measurements are devised to quantify the folding patterns. Using an MRI dataset for autism study as a test bed, we identified reduced local connectivity cost and increased curviness of gyral net bilaterally on the parietal lobe, occipital lobe, and temporal lobe in autistic patients. Additionally, we found that the cortical thickness and the gyral straightness of gyral joints are higher than the rest of gyral crest regions. The proposed representation offers a new tool for a comprehensive and reliable characterization of the cortical folding organization. This novel computational framework will enable large-scale analyses of cortical folding patterns in the future.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A new representation of cortical gyri/sulci organization pattern. </LI> <LI> A novel framework to efficiently and automatically construct gyral net from mesh surface. </LI> <LI> A new tool for a comprehensive and reliable characterization of the cortical folding organization. </LI> <LI> Enable large-scale cortical folding pattern analyses in the future. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>Illustration of the concept of gyral net and gyral joint. (a) Reconstructed cortical surface color-coded by gyral altitude. (b) Extracted gyral net. (c) Zoom in view of the circled area in (b). In this paper, we propose a new representation of cortical gyri/sulci organization pattern – gyral net, which models cortical architecture from a graph perspective, starting with nodes and edges obtained from the surface reconstructions.</P> <P>[DISPLAY OMISSION]</P>
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Wang Hong,Yang Qingyuan,Li Fangfei,Wang Huiying,Yu Jing,Ge Xihong,Gao Guangfeng,Xia Shuang,Xing Zhiheng,Shen Wen 대한의학회 2023 Journal of Korean medical science Vol.38 No.8
Background: The emergence of the severe acute respiratory syndrome coronavirus 2 omicron variant has been triggering the new wave of coronavirus disease 2019 (COVID-19) globally. However, the risk factors and outcomes for radiological abnormalities in the early convalescent stage (1 month after diagnosis) of omicron infected patients are still unknown. Methods: Patients were retrospectively enrolled if they were admitted to the hospital due to COVID-19. The chest computed tomography (CT) images and clinical data obtained at baseline (at the time of the first CT image that showed abnormalities after diagnosis) and 1 month after diagnosis were longitudinally analyzed. Uni-/multi-variable logistic regression tests were performed to explore independent risk factors for radiological abnormalities at baseline and residual pulmonary abnormalities after 1 month. Results: We assessed 316 COVID-19 patients, including 47% with radiological abnormalities at baseline and 23% with residual pulmonary abnormalities at 1-month follow-up. In a multivariate regression analysis, age ≥ 50 years, body mass index ≥ 23.87, days after vaccination ≥ 81 days, lymphocyte count ≤ 1.21 × 10-9/L, interleukin-6 (IL-6) ≥ 10.05 pg/mL and IgG ≤ 14.140 S/CO were independent risk factors for CT abnormalities at baseline. The age ≥ 47 years, presence of interlobular septal thickening and IL-6 ≥ 5.85 pg/mL were the independent risk factors for residual pulmonary abnormalities at 1-month follow-up. For residual abnormalities group, the patients with less consolidations and more parenchymal bands at baseline could progress on CT score after 1 month. There were no significant changes in the number of involved lung lobes and total CT score during the early convalescent stage. Conclusion: The higher IL-6 level was a common independent risk factor for CT abnormalities at baseline and residual pulmonary abnormalities at 1-month follow-up. There were no obvious radiographic changes during the early convalescent stage in patients with residual pulmonary abnormalities.
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A Motion Detection Approach based on UAV Image Sequence
( Hong-xia Cui ),( Ya-qi Wang ),( Fangfei Zhang ),( Tingting Li ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.3
Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.
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