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  • Open Access

    ARTICLE

    Hyperparameter Tuning Bidirectional Gated Recurrent Unit Model for Oral Cancer Classification

    K. Shankar1, E. Laxmi Lydia2, Sachin Kumar1,*, Ali S. Abosinne3, Ahmed alkhayyat4, A. H. Abbas5, Sarmad Nozad Mahmood6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4541-4557, 2022, DOI:10.32604/cmc.2022.031247

    Abstract Oral Squamous Cell Carcinoma (OSCC) is a type of Head and Neck Squamous Cell Carcinoma (HNSCC) and it should be diagnosed at early stages to accomplish efficient treatment, increase the survival rate, and reduce death rate. Histopathological imaging is a wide-spread standard used for OSCC detection. However, it is a cumbersome process and demands expert’s knowledge. So, there is a need exists for automated detection of OSCC using Artificial Intelligence (AI) and Computer Vision (CV) technologies. In this background, the current research article introduces Improved Slime Mould Algorithm with Artificial Intelligence Driven Oral Cancer Classification (ISMA-AIOCC) model on Histopathological images… More >

  • Open Access

    ARTICLE

    Transfer Learning for Disease Diagnosis from Myocardial Perfusion SPECT Imaging

    Phung Nhu Hai1, Nguyen Chi Thanh1,*, Nguyen Thanh Trung2, Tran Trung Kien1

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5925-5941, 2022, DOI:10.32604/cmc.2022.031027

    Abstract Coronary artery disease (CAD) is one of the most common pathological conditions and the major global cause of death. Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a non-invasive method and plays an essential role in diagnosing CAD. However, there is currently a shortage of doctors who can diagnose using SPECT-MPI in developing countries, especially Vietnam. Research on deploying machine learning and deep learning in supporting CAD diagnosis has been noticed for a long time. However, these methods require a large dataset and are therefore time-consuming and labor-intensive. This study aims to develop a cost-effective and high-performance… More >

  • Open Access

    ARTICLE

    Brain Tumor Detection and Classification Using PSO and Convolutional Neural Network

    Muhammad Ali1, Jamal Hussain Shah1, Muhammad Attique Khan2, Majed Alhaisoni3, Usman Tariq4, Tallha Akram5, Ye Jin Kim6, Byoungchol Chang7,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4501-4518, 2022, DOI:10.32604/cmc.2022.030392

    Abstract Tumor detection has been an active research topic in recent years due to the high mortality rate. Computer vision (CV) and image processing techniques have recently become popular for detecting tumors in MRI images. The automated detection process is simpler and takes less time than manual processing. In addition, the difference in the expanding shape of brain tumor tissues complicates and complicates tumor detection for clinicians. We proposed a new framework for tumor detection as well as tumor classification into relevant categories in this paper. For tumor segmentation, the proposed framework employs the Particle Swarm Optimization (PSO) algorithm, and for… More >

  • Open Access

    ARTICLE

    Truncation and Rounding-Based Scalable Approximate Multiplier Design for Computer Imaging Applications

    S. Rooban1,*, A. Yamini Naga Ratnam1, M. V. S. Ramprasad2, N. Subbulakshmi3, R. Uma Mageswari4

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5169-5184, 2022, DOI:10.32604/cmc.2022.027974

    Abstract Advanced technology used for arithmetic computing application, comprises greater number of approximate multipliers and approximate adders. Truncation and Rounding-based Scalable Approximate Multiplier (TRSAM) distinguish a variety of modes based on height (h) and truncation (t) as TRSAM (h, t) in the architecture. This TRSAM operation produces higher absolute error in Least Significant Bit (LSB) data shift unit. A new scalable approximate multiplier approach that uses truncation and rounding TRSAM (3, 7) is proposed to increase the multiplier accuracy. With the help of foremost one bit architecture, the proposed scalable approximate multiplier approach reduces the partial products. The proposed approximate TRSAM… More >

  • Open Access

    ARTICLE

    A Novel Handcrafted with Deep Features Based Brain Tumor Diagnosis Model

    Abdul Rahaman Wahab Sait1,*, Mohamad Khairi Ishak2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2057-2070, 2023, DOI:10.32604/iasc.2023.029602

    Abstract In healthcare sector, image classification is one of the crucial problems that impact the quality output from image processing domain. The purpose of image classification is to categorize different healthcare images under various class labels which in turn helps in the detection and management of diseases. Magnetic Resonance Imaging (MRI) is one of the effective non-invasive strategies that generate a huge and distinct number of tissue contrasts in every imaging modality. This technique is commonly utilized by healthcare professionals for Brain Tumor (BT) diagnosis. With recent advancements in Machine Learning (ML) and Deep Learning (DL) models, it is possible to… More >

  • Open Access

    ARTICLE

    Congenital Coronary Artery Fistula in Children: A Review of 28 Cases with Clinical and Imaging Outcomes

    Pornrawee Plearntummakun1, Chodchanok Vijarnsorn1,*, Kritvikrom Durongpisitkul1, Prakul Chanthong1, Paweena Chungsomprasong1, Supaluck Kanjanauthai1, Thita Pacharapakornpong1, Jarupim Soongswang1, Thaworn Subtaweesin2

    Congenital Heart Disease, Vol.17, No.4, pp. 463-478, 2022, DOI:10.32604/chd.2022.021545

    Abstract Background: Congenital coronary artery fistula (CCAF) is a rare anomaly. Treatment strategies tend to close the defect with a symptomatic and significant shunt, primarily based on expert consensus and case series. Results for long-term follow-up in children are limited Methods: We conducted a retrospective study to assess clinical and imaging outcomes of children with CCAF at Siriraj Hospital, Thailand during 2000–2020. Patients with single ventricle were excluded. Treatment strategies [surgical closure (SC), and percutaneous closure (PC)] were classified and the clinical outcomes at the follow-up in 2021, including coronary thrombosis, myocardial ischemia, and the results of cardiovascular imaging were reviewed.… More > Graphic Abstract

    Congenital Coronary Artery Fistula in Children: A Review of 28 Cases with Clinical and Imaging Outcomes

  • Open Access

    CASE REPORT

    Multimodal Imaging with 3D-Holograms for Preoperative Planning in Pediatric Cardiac Surgery: A Unique Case Report

    Federica Caldaroni1, Massimo Chessa2, Alessandro Varrica1, Alessandro Giamberti1,*

    Congenital Heart Disease, Vol.17, No.4, pp. 491-494, 2022, DOI:10.32604/chd.2022.019119

    Abstract Multimodal imaging, including augmented or mixed reality, transforms the physicians’ interaction with clinical imaging, allowing more accurate data interpretation, better spatial resolution, and depth perception of the patient’s anatomy. We successfully overlay 3D holographic visualization to magnetic resonance imaging images for preoperative decision making of a complex case of cardiac tumour in a 7-year-old girl. More >

  • Open Access

    CASE REPORT

    A Rare Case of Concordant Atrioventricular Connection to L-Looped Ventricles in Situs Solitus: 4-Dimensional Magnetic Resonance Imaging and 3D Printing

    Gregory Perens1,*, Takegawa Yoshida2, J. Paul Finn2

    Congenital Heart Disease, Vol.17, No.4, pp. 387-392, 2022, DOI:10.32604/chd.2022.021233

    Abstract An infant male presented with the rare anatomy consisting of situs solitus, concordant atrioventricular connections to L-looped ventricles, double outlet right ventricle (DORV), and hypoplastic aortic arch. 6 months after neonatal aortic arch repair, the morphologic right ventricle function deteriorated, and surgical evaluation was undertaken to determine if either biventricular repair with a systemic morphologic left ventricle or right ventricular exclusion was possible. After initial echocardiography, magnetic resonance imaging (MRI) was used to create detailed axial and 4-dimensional (4D) images and 3-dimensional (3D) printed models. The detailed anatomy of this rare, complex case and its use in pre-surgical planning is… More > Graphic Abstract

    A Rare Case of Concordant Atrioventricular Connection to L-Looped Ventricles in Situs Solitus: 4-Dimensional Magnetic Resonance Imaging and 3D Printing

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph

    Shuihua Wang1,*, Zheng Zhang2, Yuankai Huo3

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 707-709, 2022, DOI:10.32604/cmes.2022.023806

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    MicroRNA-1277 Inhibits Proliferation and Migration of Hepatocellular Carcinoma HepG2 Cells by Targeting and Suppressing BMP4 Expression and Reflects the Significant Indicative Role in Hepatocellular Carcinoma Pathology and Diagnosis After Magnetic Resonance Imaging Assessment

    Xinshan Cao*, Ling Xu, Quanyuan Liu*, Lijuan Yang, Na Li§, Xiaoxiao Li*

    Oncology Research, Vol.27, No.3, pp. 301-309, 2019, DOI:10.3727/096504018X15213058045841

    Abstract Our study aimed to investigate the roles and possible regulatory mechanism of miR-1277 in the development of hepatocellular carcinoma (HCC). HCC patients were identified from patients who were diagnosed with focal liver lesions using magnetic resonance imaging (MRI). The expression levels of miR-1277 in the serum of HCC patients and HepG2 cells were measured. Then miR-1277 mimic, miR-1277 inhibitor, or scramble RNA was transfected into HepG2 cells. The effects of miR-1277 overexpression and suppression on HepG2 cell proliferation, migration, and invasion were then investigated. Additionally, the expression levels of epithelial– mesenchymal transition (EMT)-related markers, including E-cadherin, -catenin, and vimentin, were… More >

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