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A rapid, automated flaw segmentation method using morphological reconstruction to grade wood flooring

Journal of Forestry Research 2014年第4期25卷 959-964页

作者： Yizhuo Zhang Sijia Liu Jun Cao Chao Li Huiling Yu Northeast Forestry University Zhejiang University

Region-Growing Algorithms （RGAs） are used to grade the quality of manufactured wood flooring. Traditional RGAs are hampered by prob- lems of long segmentation time and low inspection accuracy caused by neighborhood search. We used morphological reconstruction with the R com- ponent to construct a novel flaw segmentation method. We initially designed two template images for low and high thresholds, and these were used for seed optimization and inflation growth, respectively. Then the extraction of the flaw skeleton from the low threshold image was realized by applying the erosion termination rules. The seeds in the flaw skeleton were optimized by the pruning method. The geodesic inflection was applied by the high threshold template to realize rapid growth of the flaw area in the floor plate, and region filling and pruning operations were applied for margin optimization. Experi- ments were conducted on 512×512, 256×256 and 128×128 pixel sizes, re- spectively. The 256×256 pixel size proved superior in time-consumption at 0.06 s with accuracy of 100%. But with the region-growing method the same process took 0.22 s with accuracy of 70%. Compared with RGA, our pro- posed method can realize more accurate segmentation, and the speed and accuracy of segmentation can satisfy the requirements for on-line grading of wood flooring.

关键词： wood plate wood plate classification flaw segmentation region-growing morphological reconstruction

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Divergent Projection Patterns Revealed by reconstruction of Individual Neurons in Orbitofrontal Cortex

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Neuroscience Bulletin 2021年第4期37卷 461-477页

作者： Junjun Wang Pei Sun Xiaohua Lv Sen Jin Anan Li Jianxia Kuang Ning Li Yadong Gang Rui Guo Shaoqun Zeng Fuqiang Xu Yu-Hui Zhang Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and TechnologyWuhan430074China MoE Key Laboratory for Biomedical Photonics School of Engineering SciencesHuazhong University of Science and TechnologyWuhan430074China Centre for Brain Science State Key Laboratory of Magnetic Resonance and Atomic Molecular PhysicsKey Laboratory of Magnetic Resonance in Biological SystemsWuhan Institute of Physics and MathematicsCAS Centre for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesWuhan430071China

The orbitofrontal cortex(OFC)is involved in diverse brain functions via its extensive projections to multiple target *** is a growing understanding of the overall outputs of the OFC at the population level,but reports of the projection patterns of individual OFC neurons across different cortical layers remain ***,by combining neuronal sparse and bright labeling with a whole-brain florescence imaging system(fMOST),we obtained an uninterrupted three-dimensional whole-brain dataset and achieved the full morphological reconstruction of 25 OFC pyramidal *** compared the wholebrain projection targets of these individual OFC neurons in different cortical layers as well as in the same cortical *** found cortical layer-dependent projections characterized by divergent patterns for information *** study not only provides a structural basis for understanding the principles of laminar organizations in the OFC,but also provides clues for future functional and behavioral studies on OFC pyramidal neurons.

关键词： Orbitofrontal cortex Whole-brain imaging morphological reconstruction Output Projection pattern

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Research and application on corn crop identification and positioning method based on Machine vision

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Information Processing in Agriculture 2023年第1期10卷 106-113页

作者： Bingrui Xu Li Chai Chunlong Zhang College of Engineering China Agricultural UniversityQinghua Rd.(E)No.17Haidian DistrictBeijing 100083PR China International College Beijing China Agricultural UniversityQinghua Rd.(E)No.17Haidian DistrictBeijing 100083PR China

Weeds that grow among crops are undesirable plants and have adversely affected crop growth and ***,the study explores corn identification and positioning methods based on machine *** ultra-green feature algorithm and maximum betweenclass variance method(OTSU)were used to segment maize corn,weeds,and land;the segmentation effect was significant and can meet the following shape feature extraction ***,the identification and positioning of corn were achieved by morphological reconstruction and pixel projection histogram *** experiment reveals that when a weeding robot travels at a speed of 1.6 km/h,the recognition accuracy can reach 94.1%.The technique used in this study is accessible for normal cases and can make a good recognition effect;the accuracy and real-time requirements of robot recognition are improved and reduced the calculation time.

关键词： Machine vision Inter-plant weeding morphological reconstruction Target recognition

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Pathological Networks Involving Dysmorphic Neurons in Type ⅡFocal Cortical Dysplasia

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Neuroscience Bulletin 2022年第9期38卷 1007-1024页

作者： Yijie Shao Qianqian Ge Jiachao Yang Mi Wang Yu Zhou Jin-Xin Guo Mengyue Zhu Jiachen Shi Yiqi Hu Li Shen Zhong Chen Xiao-Ming Li Jun-Ming Zhu Jianmin Zhang Shumin Duan Jiadong Chen Center for Neuroscience and Department of Neurosurgery of the Second Affiliated Hospital NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Research and Brain-Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhou310058China Department of Neurosurgery of the Second Affiliated Hospital Zhejiang University School of MedicineHangzhou310009China The MOE Key Laboratory of Biosystems Homeostasis&Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology Life Sciences InstituteZhejiang UniversityHangzhou310058China Department of Orthopedic Surgery School of Medicinethe Second Affiliated HospitalZhejiang UniversityHangzhou310009China Hangzhou Innovation Center Zhejiang UniversityHangzhou310058China Institute of Pharmacology&Toxicology NHC and CAMS Key Laboratory of Medical NeurobiologyCollege of Pharmaceutical SciencesSchool of Basic Medical SciencesZhejiang UniversityHangzhou310058China Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province College of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhou310058China Center for Neuroscience and Department of Neurology of the Second Affiliated Hospital Zhejiang University School of MedicineHangzhou310058China NHC and CAMS Key Laboratory of Medical Neurobiology Center for Brain Science and Brain-Inspired IntelligenceJoint Institute for Genetics and Genome Medicine betweenGuangdong Hong Kong Macao Greater Bay AreaZhejiang University and the University of TorontoZhejiang University School of MedicineHangzhou310058China

Focal cortical dysplasia(FCD)is one of the most common causes of drug-resistant *** neurons are the major histopathological feature of typeⅡFCD,but their role in seizure genesis in FCD is *** we performed whole-cell patch-clamp recording and morphological reconstruction of cortical principal neurons in postsurgical brain tissue from drug-resistant epilepsy *** analyses revealed distinct morphological and electrophysiological characteristics of the upper layer dysmorphic neurons in typeⅡFCD,including an enlarged soma,aberrant dendritic arbors,increased current injection for rheobase action potential firing,and reduced action potential firing ***,the upper layer dysmorphic neurons received decreased glutamatergic and increased GABAergic synaptic inputs that were coupled with upregulation of the Na^(+)-K^(+)-Cl^(−)*** addition,we found a depolarizing shift of the GABA reversal potential in the CamKⅡ-cre::PTENflox/flox mouse model of drug-resistant epilepsy,suggesting that enhanced GABAergic inputs might depolarize dysmorphic ***,imbalance of synaptic excitation and inhibition of dysmorphic neurons may contribute to seizure genesis in typeⅡFCD.

关键词： Focal cortical dysplasia Dysmorphic neuron Whole-cell patch-clamp recording morphological reconstruction Excitation-inhibition balance

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SWM-DE:Statistical wavelet model for joint denoising and enhancement for multimodal medical images

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Medicine in Novel Technology and Devices 2023年第2期18卷 206-214页

作者： Idowu Paul Okuwobi Zhixiang Ding Jifeng Wan Jiajia Jiang School of Artificial Intelligence Guilin University of Electronic Technology#1 Jinji RoadGuilin541004China Department of Ophthalmology Affiliated Hospital of Guilin Medical University1#Zhiyuan RdGuilin541199China

Medical images are usually degraded by numerous noises during acquisition or transmission,which often causes low contrast leading to deterioration of image *** such,medical image denoising and enhancement has become a paramount routine *** overcome this problem,we propose a cutting-edge joint statistical and morphological model for the denoising and enhancement ***,we propose a statistical model in formulating the marginal distribution of the wavelet *** model is integrated into a Bayesian inference framework to develop a maximum a posterior(MAP)estimator of the noise-free *** on the statistical model,we eliminate the need for noise level estimation,and allows the model to automatically adapts to the observed image ***,we propose an adjustable morphological reconstruction model to eliminate known and unknown noises associated with medical images,while preserving the image *** these operations,the image is decomposed into several wavelet subbands to extract the illumination and detail *** image is then reconstructed based on the inverse wavelet to generate the enhanced noise-free *** results show that the proposed framework obtained high EME values of 41.04,48.81,47.81,and 45.75 for OCTA,FFA,CT,and X-ray imaging modalities,and performs better than the state-of-the-art *** proposed algorithm can effectively and efficiently enhance medical images,which will assist the clinicians in disease diagnosis,monitoring,and treatment.

关键词： Computer tomography morphological reconstruction Medical images Wavelets transform

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