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Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer modeling in Engineering & Sciences 2024年第8期140卷 1539-1562页

作者： samar m.Alqhtani Toufique A.Soomro Faisal Bin Ubaid Ahmed Ali muhammad Irfan Abdullah A.Asiri Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer Science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various *** resonance imaging(mRI)and computed tomography(CT)are utilized to capture brain *** plays a crucial role in the diagnosis of brain tumors and the examination of other brain ***,manual assessment of mRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely ***,early diagnosis of brain tumors is intricate,necessitating the use of computerized *** research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain *** proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-means(FCm)clustering technique in the third *** final step involves classification using the Support Vector machine(SVm)*** classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced magnetic Resonance Imaging(CE-mRI)*** proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of ***,this method exhibits a shorter processing time of 0.44 s compared to existing *** performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and *** enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classi

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

Unique presentation of neonatal liver failure:A case report

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World Journal of Clinical Pediatrics 2024年第2期13卷 221-226页

作者： Eman Al Atrash Amer Azaz samar Said mohammad miqdady Department of Pediatrics Division of Pediatric GastroenterologySheikh Khalifa Medical CityAbu Dhabi 971United Arab Emirates Department of Pathology Mayo ClinicRochesterMN 55905United States

BACKGROUND Acute fulminant liver failure rarely occurs in the neonatal *** etiologies include viral infection(15%),metabolic/genetic disease(10%),hematologic disorders(15%),and ischemic injury(5%).Gestational alloimmune liver disease usually manifests as severe neonatal liver failure,with extensive hepatic and extrahepatic iron overload,sparing the reticuloendothelial *** liver failure is a rare cause of liver failure where a patient presents with liver failure in the neonatal period with no hepatocytes in liver *** SUmmARY A 5-week-old male presented with *** examination revealed an alert but deeply icteric *** data demonstrated direct hyperbilirubinemia,a severely deranged coagulation profile,normal transaminase,and normal *** resonance imaging of the abdomen was suggestive of perinatal *** biopsy showed histiocytic infiltration with an absence of *** hemosiderin deposition was identified in a buccal mucosa *** Neonatal liver failure in the absence of hepatocellular regeneration potentially reflects an acquired or inborn defect in the regulation of hepatic regeneration.

关键词： Liver Hyperbilirubinemia Le foie vide Neonatal hemochromatosis Case report

Case Report and Clinical management of a Case of Osteogenesis Imperfecta Detected in the Prenatal Period

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Open Journal of Obstetrics and Gynecology 2024年第7期14卷 996-1002页

作者： Amina Chaieb Oumayma Ben Rejeb samar Knaz Yasmine Ben Ali Syrine Chelly Safia Ernez mouna Derouiche Department of Gynecology and Obstetrics Farhat Hached University Hospital Sousse Tunisia Faculty of medicine Ibn Al Jazzar University of Sousse Sousse Tunisia

Osteogenesis imperfecta is a hereditary disease characterized by bone fragility due to a defect in type I collagen synthesis. The diagnosis is typically suspected based on suggestive ultrasound findings and confirmed through genetic studies. We present a case of osteogenesis imperfecta suspected during obstetrical ultrasound at 19 weeks’ gestation, which was later confirmed radiographically through computed tomography. Due to the severity of the condition, therapeutic termination of pregnancy was indicated.

关键词： Osteogenesis Imperfecta Ultrasound Screening Antenatal Diagnosis

An Automated Real-Time Face mask Detection System Using Transfer Learning with Faster-RCNN in the Era of the COVID-19 Pandemic

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Computers, materials & Continua 2022年第5期71卷 4151-4166页

作者： maha Farouk S.Sabir Irfan mehmood Wafaa Adnan alsaggaf Enas Fawai Khairullah samar Alhuraiji Ahmed S.Alghamdi Ahmed A.Abd El-Latif Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversitySaudi Arabia Centre for Visual Computing Faculty of Engineering and InformaticsUniversity of BradfordBradfordU.K Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahP.O.Box 23713Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of mathematics and Computer Science Faculty of ScienceMenoufia University32511Egypt

Today,due to the pandemic of COVID-19 the entire world is facing a serious health *** to the World Health Organization(WHO),people in public places should wear a face mask to control the rapid transmission of *** governmental bodies of different countries imposed that wearing a face mask is compulsory in public ***,it is very difficult to manually monitor people in overcrowded *** research focuses on providing a solution to enforce one of the important preventative measures of COVID-19 in public places,by presenting an automated system that automatically localizes masked and unmasked human faces within an image or video of an area which assist in this outbreak of *** paper demonstrates a transfer learning approach with the Faster-RCNN model to detect faces that are masked or *** proposed framework is built by fine-tuning the state-of-the-art deep learning model,Faster-RCNN,and has been validated on a publicly available dataset named Face mask Dataset(FmD)and achieving the highest average precision(AP)of 81%and highest average Recall(AR)of 84%.This shows the strong robustness and capabilities of the Faster-RCNN model to detect individuals with masked and un-masked ***,this work applies to real-time and can be implemented in any public service area.

关键词： COIVD-19 deep learning faster-RCNN object detection transfer learning face mask

A Hybrid model for Reliability Aware and Energy-Efficiency in multicore Systems

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Computers, materials & Continua 2022年第3期70卷 4447-4466页

作者： samar Nour Sameh A.Salem Shahira m.Habashy Department of Computer and Systems Engineering Faculty of EngineeringHelwan UniversityCairo11792Egypt Egyptian Computer Emergency Readiness Team(EG-CERT) National Telecom Regulatory Authority(NTRA)Cairo12577Egypt

Recently,multicore systems use Dynamic Voltage/Frequency Scaling(DV/FS)technology to allow the cores to operate with various voltage and/or frequencies than other cores to save power and enhance the *** this paper,an effective and reliable hybridmodel to reduce the energy and makespan in multicore systems is *** proposed hybrid model enhances and integrates the greedy approach with dynamic programming to achieve optimal Voltage/Frequency(Vmin/F)***,the allocation process is applied based on the *** hybrid model consists of three *** first stage gets the optimum safe voltage while the second stage sets the level of energy efficiency,and finally,the third is the allocation *** results on various benchmarks show that the proposed model can generate optimal solutions to save energy while minimizing the makespan *** with other competitive algorithms show that the proposed model provides on average 48%improvements in energy-saving and achieves an 18%reduction in computation time while ensuring a high degree of system reliability.

关键词： Energy-efficiency safe voltage multicore processors core utilization dynamic voltage/frequency scaling makespan

A need for stratification of metastasis samples according to secondary site in gene expression studies

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BIOCELL 2022年第7期46卷 1747-1750页

作者： IVANA samarŽIJA Laboratory for Epigenomics Division of Molecular MedicineRuđer BoškovićInstituteZagreb10000Croatia Laboratory for Cell Biology and Signaling Division of Molecular BiologyRuđer BoškovićInstituteZagreb10000Croatia

Comparisons of gene expression profiles between primary tumors and metastasis have revealed genes that are implicated in metastasis ***,gene expression studies conducted on metastasis samples from the same primary site usually do not discriminate between different secondary *** the change in the expression of number of genes is expected to be common to metastasis from the same primary but different secondary sites,herein the data that point to substantial differences are ***,the reciprocal communication between metastatic and host cells that is influencing these differences is outlined to emphasize the need for stratification of metastasis samples in gene expression studies.

关键词： Bone metastasis Brain metastasis Liver metastasis Lung metastases Gene expression

Efficient Image Captioning Based on Vision Transformer models

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Computers, materials & Continua 2022年第10期73卷 1483-1500页

作者： samar Elbedwehy T.medhat Taher Hamza mohammed F.Alrahmawy Department of Data Science Faculty of Artificial IntelligenceKafrelsheikh UniversityEgypt Department of Electrical Engineering Faculty of EngineeringKafrelsheikh UniversityEgypt Department of Computer Science Faculty of Computer and Information ScienceMansouraEgypt

Image captioning is an emerging field in machine *** refers to the ability to automatically generate a syntactically and semantically meaningful sentence that describes the content of an *** captioning requires a complex machine learning process as it involves two sub models:a vision sub-model for extracting object features and a language sub-model that use the extracted features to generate meaningful ***-based vision transformers models have a great impact in vision field *** this paper,we studied the effect of using the vision transformers on the image captioning process by evaluating the use of four different vision transformer models for the vision sub-models of the image captioning The first vision transformers used is DINO(self-distillation with no labels).The second is PVT(Pyramid Vision Transformer)which is a vision transformer that is not using convolutional *** third is XCIT(cross-Covariance Image Transformer)which changes the operation in self-attention by focusing on feature dimension instead of token *** last one is SWIN(Shifted windows),it is a vision transformer which,unlike the other transformers,uses shifted-window in splitting the *** a deeper evaluation,the four mentioned vision transformers have been tested with their different versions and different configuration,we evaluate the use of DINO model with five different backbones,PVT with two versions:PVT_v1and PVT_v2,one model of XCIT,SWIN *** results show the high effectiveness of using SWIN-transformer within the proposed image captioning model with regard to the other models.

关键词： Image captioning sequence-to-sequence self-distillation transformer convolutional layer

A U-Net-Based CNN model for Detection and Segmentation of Brain Tumor

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Computers, materials & Continua 2023年第1期74卷 1333-1349页

作者： Rehana Ghulam Sammar Fatima Tariq Ali Nazir Ahmad Zafar Abdullah A.Asiri Hassan A.Alshamrani samar m.Alqhtani Khlood m.mehdar Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Radiological Sciences Department College of applied medical sciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajran61441Saudi Arabia

Human brain consists of millions of cells to control the overall structure of the human *** these cells start behaving abnormally,then brain tumors *** and initial stage brain tumor detection has always been an issue in the field of medicines for medical *** handle this issue,various deep learning techniques for brain tumor detection and segmentation techniques have been developed,which worked on different datasets to obtain fruitful results,but the problem still exists for the initial stage of detection of brain tumors to save human *** this purpose,we proposed a novel U-Net-based Convolutional Neural Network(CNN)technique to detect and segmentizes the brain tumor for magnetic Resonance Imaging(mRI).moreover,a 2-dimensional publicly available multimodal Brain Tumor Image Segmentation(BRATS2020)dataset with 1840 mRI images of brain tumors has been used having an image size of 240×240 *** initial dataset preprocessing the proposed model is trained by dividing the dataset into three parts i.e.,testing,training,and validation *** model attained an accuracy value of 0.98%on the BRATS2020 dataset,which is the highest one as compared to the already existing techniques.

关键词： U-net brain tumor magnetic resonance images convolutional neural network segmentation

molecular mechanisms targeting drug-resistance and metastasis in colorectal cancer:Updates and beyond

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World Journal of Gastroenterology 2023年第9期29卷 1395-1426页

作者： samar Al Bitar marwan El-Sabban Samer Doughan Wassim Abou-Kheir Department of Anatomy Cell Biology and Physiological SciencesAmerican University of BeirutBeirut 1107-2020Lebanon Department of Surgery American University of Beirut Medical CenterBeirut 1107-2020Lebanon

Colorectal cancer(CRC)is the third most diagnosed malignancy and a major leading cause of cancer-related deaths *** advances in therapeutic regimens,the number of patients presenting with metastatic CRC(mCRC)is increasing due to resistance to therapy,conferred by a small population of cancer cells,known as cancer stem *** therapies have been highly successful in prolonging the overall survival of patients with *** are being developed to target key molecules involved in drug-resistance and metastasis of CRC,and these include vascular endothelial growth factor,epidermal growth factor receptor,human epidermal growth factor receptor-2,mitogen-activated extracellular signal-regulated kinase,in addition to immune ***,there are several ongoing clinical trials of newly developed targeted agents,which have shown considerable clinical efficacy and have improved the prognosis of patients who do not benefit from conventional *** this review,we highlight recent developments in the use of existing and novel targeted agents against drug-resistant CRC and ***,we discuss limitations and challenges associated with targeted therapy and strategies to combat intrinsic and acquired resistance to these therapies,in addition to the importance of implementing better preclinical models and the application of personalized therapy based on predictive biomarkers for treatment selection.

关键词： Colorectal cancer metastatic colorectal cancer Targeted therapy Drugresistance Personalized medicine