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computer-assisted three-dimensional individualized extreme liver resection for hepatoblastoma in proximity to the major liver vasculature

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World Journal of Gastrointestinal surgery 2024年第4期16卷 1066-1077页

作者： Wen-Li Xiu Jie Liu Jing-Li Zhang Jing-Miao Wang Xue-Feng Wang Fei-Fei Wang Jie Mi Xi-Wei Hao NanXia Qian Dong Department of Pediatric surgery The Affiliated Hospital of Qingdao UniversityQingdao 266000Shandong ProvinceChina Department of Pediatric surgery Yijishan Hospital of Wannan Medical CollegeWuhu 241000Anhui ProvinceChina shandong Provincial key laboratory of digital medicine and computer-assisted surgery Shandong College Collaborative Innovation Center of Digital Medicine Clinical Treatment and Nutrition HealthQingdao UniversityQingdao 266003Shandong ProvinceChina

BACKGROUND The management of hepatoblastoma(HB)becomes challenging when the tumor remains in close proximity to the major liver vasculature(PMV)even after a full course of neoadjuvant chemotherapy(NAC).In such cases,extreme liver resection can be considered a potential option.AIM To explore whether computer-assisted three-dimensional individualized extreme liver resection is safe and feasible for children with HB who still have PMV after a full course of NAC.METHODS We retrospectively collected data from children with HB who underwent surgical resection at our center from June 2013 to June 2023.We then analyzed the detailed clinical and three-dimensional characteristics of children with HB who still had PMV after a full course of NAC.RESULTS Sixty-seven children diagnosed with HB underwent surgical resection.The age at diagnosis was 21.4±18.8 months,and 40 boys and 27 girls were included.Fifty-nine(88.1%)patients had a single tumor,39(58.2%)of which was located in the right lobe of the liver.A total of 47 patients(70.1%)had PRE-TEXT III or IV.Thirty-nine patients(58.2%)underwent delayed resection.After a full course of NAC,16 patients still had close PMV(within 1 cm in two patients,touching in 11 patients,compressing in four patients,and showing tumor thrombus in three patients).There were 6 patients of tumors in the middle lobe of the liver,and four of those patients exhibited liver anatomy variations.These 16 children underwent extreme liver resection after comprehensive preoperative evaluation.Intraoperative procedures were performed according to the preoperative plan,and the operations were successfully performed.Currently,the 3-year event-free survival of 67 children with HB is 88%.Among the 16 children who underwent extreme liver resection,three experienced recurrence,and one died due to multiple metastases.CONCLUSION Extreme liver resection for HB that is still in close PMV after a full course of NAC is both safe and feasible.This approach not only reduces the necessity for liver transplantation but also r

关键词： Children Hepatoblastoma surgery Three-dimensional computer-assisted

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Automatic recognition of depression based on audio and video:A review

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World Journal of Psychiatry 2024年第2期14卷 225-233页

作者： Meng-Meng Han Xing-Yun Li Xin-Yu Yi Yun-Shao Zheng Wei-Li Xia Ya-Fei Liu Qing-Xiang Wang shandong Mental Health Center Shandong UniversityJinan 250014Shandong ProvinceChina key laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353Shandong ProvinceChina shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and TechnologyQilu University of Technology(Shandong Academy of Sciences)Jinan 250353Shandong ProvinceChina shandong Provincial key laboratory of computer Networks Shandong Fundamental Research Center for Computer ScienceJinan 250353Shandong ProvinceChina Department of Ward Two Shandong Mental Health CenterShandong UniversityJinan 250014Shandong ProvinceChina

Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression assessment.Non-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively utilized.Specialized physicians usually require extensive training and experience to capture changes in these features.Advancements in deep learning technology have provided technical support for capturing non-biological markers.Several researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression screening.This article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.

关键词： Depression recognition Deep learning Automatic depression estimation System Audio processing Image processing Feature fusion Future development

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Effect of granular shape on radial segregation in a two-dimensional drum

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Chinese Physics B 2024年第4期33卷 509-514页

作者：徐悦李然迟志鹏修文正孙其诚杨晖 School of Optical-Electrical and computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Electrical and Electronic Engineering Shandong University of TechnologyZibo 255049China State key laboratory of Hydroscience and Engineering Tsinghua UniversityBeijing 100084China College of Medical Instruments Shanghai University of Medicine and Health SciencesShanghai 201318China

Granular segregation is widely observed in nature and industry.Most research has focused on segregation caused by differences in the size and density of spherical grains.However,due to the fact that grains typically have different shapes,the focus is shifting towards shape segregation.In this study,experiments are conducted by mixing cubic and spherical grains.The results indicate that spherical grains gather at the center and cubic grains are distributed around them,and the degree of segregation is low.Through experiments,a structured analysis of local regions is conducted to explain the inability to form stable segregation patterns with obviously different geometric shapes.Further,through simulations,the reasons for the central and peripheral distributions are explained by comparing velocities and the number of collisions of the grains in the flow layer.

关键词： granular materials cubic grains shape segregation segregation mechanism

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A CSMA/CA based MAC protocol for hybrid Power-line/Visible-light communication networks:Design and analysis

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digital Communications and Networks 2024年第2期10卷 481-497页

作者： Sheng Hao Huyin Zhang Fei Yang Chenghao Li Jing Wang School of computer Science Central China Normal UniversityWuhan430079PR China Hubei key laboratory of intelligent Robot(Wuhan Institute of Technology) Wuhan430079PR China School of computer Science Wuhan UniversityWuhan430079China School of Information Science and Engineering Shandong Normal UniversityJinan250000China School of computer Science Hubei University of TechnologyWuhan430079China

Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and hardware efficiency.Current research on HPVC networks focuses on the performance analysis and optimization of the Physical(PHY)layer,where the Power Line Communication(PLC)component only serves as the backbone to provide power to light Emitting Diode(LED)devices.So designing a Media Access Control(MAC)protocol remains a great challenge because it allows both PLC and Visible Light Communication(VLC)components to operate data transmission,i.e.,to achieve a true HPVC network CC.To solve this problem,we propose a new HPC network MAC protocol(HPVC MAC)based on Carrier Sense Multiple Access/Collision Avoidance(CSMA/CA)by combining IEEE 802.15.7 and IEEE 1901 standards.Firstly,we add an Additional Assistance(AA)layer to provide the channel selection strategies for sensor stations,so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism,respectively.Based on this,we give a detailed working principle of the HPVC MAC,followed by the construction of a joint analytical model for mathematicalmathematical validation of the HPVC MAC.In the modeling process,the impacts of PHY layer settings(including channel fading types and additive noise feature),CSMA/CA mechanisms of 802.15.7 and 1901,and practical configurations(such as traffic rate,transit buffer size)are comprehensively taken into consideration.Moreover,we prove the proposed analytical model has the solvability.Finally,through extensive simulations,we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62%between the simulation and analytical results.

关键词： Hybrid power-line/Visible light communication (HPVC)networks MAC protocol CSMA/CA IEEE 802.15.7 IEEE 1901 Performance analysis

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Development and application of a detection platform for colorectal cancer tumor sprouting pathological characteristics based on artificial intelligence

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Intelligent medicine 2022年第2期2卷 82-87页

作者： Jiaqi Lu Ruiqing Liu Yuejuan Zhang Xianxiang Zhang Longbo Zheng Chao Zhang Kaiming Zhang Shuai Li Yun Lu Department of Gastrointestinal surgery Affiliated Hospital of Qingdao UniversityQingdaoShandong 266055China Department of Pathology Affiliated Hospital of Qingdao UniversityQingdaoShandong 266003China State key laboratory of Virtual Reality Technology and System Beihang UniversityBeijing 100191China shandong Provincial key laboratory of digital medicine and computer assisted surgery QingdaoShandong 266003China Research Institute of digital medicine and computer Aided surgery Qingdao UniversityQingdaoShandong 266000China

Objective Tumor sprouting can reflect independent risk factors for tumor malignancy and a poor clinical progno-sis.However,there are significant differences and difficulties associated with manually identifying tumor sprout-ing.This study used the Faster region convolutional neural network(RCNN)model to build a colorectal cancer tumor sprouting artificial intelligence recognition framework based on pathological sections to automatically identify the budding area to assist in the clinical diagnosis and treatment of colorectal cancer.Methods We retrospectively collected 100 surgical pathological sections of colorectal cancer from January 2019 to October 2019.The pathologists used LabelImg software to identify tumor buds and to count their numbers.Finally,1,000 images were screened,and the total number of tumor buds was approximately 3,226;the images were randomly divided into a training set and a test set at a ratio of 6:4.After the images in the training set were manually identified,the identified buds in the 600 images were used to train the Faster RCNN identification model.After the establishment of the artificial intelligence identification detection platform,400 images in the test set were used to test the identification detection system to identify and predict the area and number of tumor buds.Finally,by comparing the results of the Faster RCNN system and the identification information of pathologists,the performance of the artificial intelligence automatic detection platform was evaluated to determine the area and number of tumor sprouting in the pathological sections of the colorectal cancers to achieve an auxiliary diagnosis and to suggest appropriate treatment.The selected performance indicators include accuracy,precision,specificity,etc.ROC(receiver operator characteristic)and AUC(area under the curve)were used to quantify the performance of the system to automatically identify tumor budding areas and numbers.Results The AUC of the receiver operating characteristic curve of the artificial intelligence de

关键词： Artificial intelligence Tumor budding Colorectal cancer Pathological section

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computer-assisted rescue of the inferior mesenteric artery in a child with a giant ganglioneuroblastoma: A case report

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World Journal of Gastrointestinal surgery 2023年第5期15卷 984-991页

作者： Wen-Li Xiu Jie Liu Jing-Li Zhang Nan Su Feng-Jiao Wang Xi-Wei Hao Fei-Fei Wang Qian Dong Department of Pediatric surgery The Affiliated Hospital of Qingdao UniversityQingdao 266000Shandong ProvinceChina shandong Provincial key laboratory of digital medicine and computer-assisted surgery Shandong College Collaborative Innovation Center of Digital Medicine Clinical Treatment and Nutrition HealthQingdao UniversityQingdao 266003Shandong ProvinceChina Department of Pediatric surgery Yijishan Hospital of Wannan Medical CollegeWuhu 241000Anhui ProvinceChina

BACKGROUND Ganglioneuroblastoma(GNB)is a peripheral neuroblastoma(NB)with malignant degree between highly malignant NB and benign ganglioma(GN).Pathology is the gold standard of diagnosis.Although GNB is not uncommon in children,biopsy alone may lead to an inaccurate diagnosis,especially for giant tumors.However,surgical resection may be associated with significant complications.Here,we report a case of computer-assisted surgical resection of a giant GNB in a child and successful rescue of the inferior mesenteric artery.CASE SUMMARY A 4-year-old girl was admitted to our department for a giant retroperitoneal lesion,which was considered to be an NB by her local hospital.The symptoms of the girl disappeared spontaneously without treatment.On physical examination,a mass of about 10 cm×7 cm could be palpated in her abdomen.Ultrasonography and contrast-enhanced computed tomography performed in our hospital also showed an NB,and there was a very thick blood vessel inside the tumor.However,aspiration biopsy revealed GN.Surgical resection is the best treatment option for this giant benign tumor.For precise preoperative evaluation,threedimensional reconstruction was performed.It was clear that the tumor was close to the abdominal aorta.The superior mesenteric vein was pushed forward,and the inferior mesenteric artery passed through the tumor.Because GN generally does not invade blood vessels,we split the tumor with a CUSA knife during the operation and found that there was indeed a straight and intact vascular sheath.Arterial pulsation was observed in the completely exposed inferior mesenteric artery.The pathologists interpreting the tissue finally diagnosed it as a mixed GNB(GNBi),which is more malignant than GN.However,both GN and GNBi usually have a good prognosis.CONCLUSION This was a case of successful surgical resection of a giant GNB,and aspiration biopsy underestimated the pathological staging of the tumor.Preoperative three-dimensional reconstruction assisted with the radical resection of the tumor and rescue of

关键词： surgery Children Ganglioneuroblastoma computer-assisted Tumor Case report

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Enhanced Temporal Correlation for Universal Lesion Detection

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computer Modeling in Engineering & Sciences 2024年第3期138卷 3051-3063页

作者： Muwei Jian Yue Jin Hui Yu School of computer Science and Technology Shandong University of Finance and EconomicsJinanChina School of Information Science and Technology Linyi UniversityLinyiChina School of Creative Technologies University of PortsmouthPortsmouthUK

Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.

关键词： Universal lesion detection computational biology medical computing deep learning enhanced temporal correlation

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Artificial intelligence recognition of pathological T stage and tumor invasion in rectal cancer based on large panoramic pathological sections

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Intelligent medicine 2022年第3期2卷 141-151页

作者： Yiheng Ju Longbo Zheng Peng Zhao Fangjie Xin Fengjiao Wang Yuan Gao Xianxiang Zhang Dongsheng Wang Yun Lu Department of General surgery Medical CenterAffiliated Hospital of Qingdao UniversityQingdaoShandong 266000China Department of Pathology Affiliated Hospital of Qingdao UniversityQingdaoShandong 266000China shandong key laboratory of digital medicine and computer assisted surgery QingdaoShandong 266071China Hainan Branch of Affiliated Hospital of Qingdao University Lingshui Li Autonomous CountyHainan 572400China

Background The incidence of colorectal cancer is increasing worldwide,and it currently ranks third among all cancers.Moreover,pathological diagnosis is becoming increasingly arduous.Artificial intelligence has demon-strated the ability to fully excavate image features and assist doctors in making decisions.Large panoramic patho-logical sections contain considerable amounts of pathological information.In this study,we used large panoramic pathological sections to establish a deep learning model to assist pathologists in identifying cancerous areas on whole-slide images of rectal cancer,as well as for T staging and prognostic analysis.Methods We collected 126 cases of primary rectal cancer from the Affiliated Hospital of Qingdao University West Coast Hospital District(internal dataset)and 42 cases from Shinan and Laoshan Hospital District(external dataset)that had tissue surgically removed from January to September 2019.After sectioning,staining,and scanning,a total of 2350 hematoxylin-eosin-stained whole-slide images were obtained.The patients in the internal dataset were randomly divided into a training cohort(n=88)and a test cohort(n=38)at a ratio of 7:3.We chose DeepLabV3+and ResNet50 as target models for our experiment.We used the Dice similarity coefficient,accuracy,sensitivity,specificity,receiver operating characteristic(ROC)curve,and area under the curve(AUC)to evaluate the performance of the artificial intelligence platform in the test set and validation set.Finally,we followed up patients and examined their prognosis and short-term survival to corroborate the value of T-staging investigations.Results In the test set,the accuracy of image segmentation was 95.8%,the Dice coefficient was 0.92,the accuracy of automatic T-staging recognition was 86%,and the ROC AUC value was 0.93.In the validation set,the accuracy of image segmentation was 95.3%,the Dice coefficient was 0.90,the accuracy of automatic classification was 85%,the ROC AUC value was 0.92,and the image analysis time was 0.2 s.There was a difference

关键词： Large panoramic pathological sections Rectal cancer Whole-slide imaging Deep learning Survival analysis

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CToMP: a cycle-task-oriented memory protection scheme for unmanned systems

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Science China(Information Sciences) 2024年第6期67卷 399-417页

作者： Chengyan MA Ning XI Di LU Yebo FENG Jianfeng MA School of Cyber Engineering Xidian University School of computer Science and Technology Xidian University Department of computer and Information Science University of Oregon

Memory corruption attacks(MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and performance.MCAs in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms,we found that MCAs are mainly categorized into two types — return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection(CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CTo MP resists the return-oriented programming(ROP) attack, a novel variant of return2libc attacks. Finally, we implement CTo MP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CTo MP is resilient to various MCAs in unmanned systems with low footprints and system overhead.

关键词： unmanned system memory corruption attack memory protection system security randomized memory address

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Quasi-Developable B-Spline Surface Design with Control Rulings

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Journal of computer Science & Technology 2022年第5期37卷 1221-1238页

作者：胡梓轩伯彭波张彩明 School of computer Science and Technology Harbin Institute of TechnologyWeihai 264209China shandong Co-Innovation Center of Future Intelligent Computing Yantai 264005China shandong Province key laboratory of digital Media Technology Shandong University of Finance and EconomicsJinan 250061China

We propose a method for generating a ruled B-spline surface fitting to a sequence of pre-defined ruling lines and the generated surface is required to be as-developable-as-possible.Specifically,the terminal ruling lines are treated as hard constraints.Different from existing methods that compute a quasi-developable surface from two boundary curves and cannot achieve explicit ruling control,our method controls ruling lines in an intuitive way and serves as an effective tool for computing quasi-developable surfaces from freely-designed rulings.We treat this problem from the point of view of numerical optimization and solve for surfaces meeting the distance error tolerance allowed in applications.The performance and the efficacy of the proposed method are demonstrated by the experiments on a variety of models including an application of the method for path planning in 5-axis computer numerical control(CNC)flank milling.

关键词： developable surface surface modeling B-spline surface numerical optimization

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