Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (48)
  • Open Access

    ARTICLE

    Xception-Fractalnet: Hybrid Deep Learning Based Multi-Class Classification of Alzheimer’s Disease

    Mudiyala Aparna, Battula Srinivasa Rao*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6909-6932, 2023, DOI:10.32604/cmc.2023.034796

    Abstract Neurological disorders such as Alzheimer’s disease (AD) are very challenging to treat due to their sensitivity, technical challenges during surgery, and high expenses. The complexity of the brain structures makes it difficult to distinguish between the various brain tissues and categorize AD using conventional classification methods. Furthermore, conventional approaches take a lot of time and might not always be precise. Hence, a suitable classification framework with brain imaging may produce more accurate findings for early diagnosis of AD. Therefore in this paper, an effective hybrid Xception and Fractalnet-based deep learning framework are implemented to classify… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Models for Magnetic Resonance Imaging (MRI)-Based Brain Tumor Classification

    Abdullah A. Asiri1, Bilal Khan2, Fazal Muhammad3,*, Shams ur Rahman4, Hassan A. Alshamrani1, Khalaf A. Alshamrani1, Muhammad Irfan5, Fawaz F. Alqhtani1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 299-312, 2023, DOI:10.32604/iasc.2023.032426

    Abstract In the medical profession, recent technological advancements play an essential role in the early detection and categorization of many diseases that cause mortality. The technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of humans. Automatic (computerized) illness detection in medical imaging has found you the emergent region in several medical diagnostic applications. Various diseases that cause death need to be identified through such techniques and technologies to overcome the mortality ratio. The brain tumor is one of the most common causes of death. Researchers have already proposed… More >

  • Open Access

    ARTICLE

    Comparison of IDEAL-IQ and IVIM-DWI for Differentiating between Alpha Fetoprotein-Negative Hepatocellular Carcinoma and Focal Nodular Hyperplasia

    Shaopeng Li, Peng Wang, Jun Qiu, Yiju Xie, Dawei Yin, Kexue Deng*

    Oncologie, Vol.24, No.3, pp. 527-538, 2022, DOI:10.32604/oncologie.2022.022815

    Abstract Background: To compare the differential diagnostic value of iterative decomposition of water and fat with the echo asymmetrical and least-squares estimation quantitation sequence (IDEAL-IQ) with that of intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) in differentiating between alpha fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) and focal nodular hyperplasia (FNH). Materials and Methods: A total of 28 AFP-negative HCC cases and 15 FNH cases were scanned using the IDEAL-IQ and IVIM-DWI magnetic resonance imaging (MRI) protocols. Two radiologists independently assessed the fat fraction (FF) and the iron level surrogate (R2*) derived from the IDEAL-IQ images and the apparent diffusion… More >

  • Open Access

    ARTICLE

    Non Sub-Sampled Contourlet with Joint Sparse Representation Based Medical Image Fusion

    Kandasamy Kittusamy*, Latha Shanmuga Vadivu Sampath Kumar

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1989-2005, 2023, DOI:10.32604/csse.2023.026501

    Abstract Medical Image Fusion is the synthesizing technology for fusing multimodal medical information using mathematical procedures to generate better visual on the image content and high-quality image output. Medical image fusion represents an indispensible role in fixing major solutions for the complicated medical predicaments, while the recent research results have an enhanced affinity towards the preservation of medical image details, leaving color distortion and halo artifacts to remain unaddressed. This paper proposes a novel method of fusing Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) using a hybrid model of Non Sub-sampled Contourlet Transform (NSCT) and… 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… 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 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

    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… More >

  • Open Access

    ARTICLE

    The Usefulness of Pretreatment MR-Based Radiomics on Early Response of Neoadjuvant Chemotherapy in Patients With Locally Advanced Nasopharyngeal Carcinoma

    Piao Yongfeng*†‡§1, Jiang Chuner*¶#1, Wang Lei*†‡§, Yan Fengqin*†‡§, Ye Zhimin*†‡§, Fu Zhenfu*†‡§, Jiang Haitao*,**††, Jiang Yangming‡‡, Wang Fangzheng*†‡§

    Oncology Research, Vol.28, No.6, pp. 605-613, 2020, DOI:10.3727/096504020X16022401878096

    Abstract The aim of this study was to explore the predictive role of pretreatment MRI-based radiomics on early response of neoadjuvant chemotherapy (NAC) in locoregionally advanced nasopharyngeal carcinoma (NPC) patients. Between January 2016 and December 2016, a total of 108 newly diagnosed NPC patients who were hospitalized in the Cancer Hospital of the University of Chinese Academy of Sciences were reviewed. All patients had complete data of enhanced MR of nasopharynx before treatment, and then received two to three cycles of TP-based NAC. After 2 cycles of NAC, enhanced MR of nasopharynx was conducted again. Compared… More >

  • Open Access

    ARTICLE

    Cartesian Product Based Transfer Learning Implementation for Brain Tumor Classification

    Irfan Ahmed Usmani1,*, Muhammad Tahir Qadri1, Razia Zia1, Asif Aziz2, Farheen Saeed3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4369-4392, 2022, DOI:10.32604/cmc.2022.030698

    Abstract Knowledge-based transfer learning techniques have shown good performance for brain tumor classification, especially with small datasets. However, to obtain an optimized model for targeted brain tumor classification, it is challenging to select a pre-trained deep learning (DL) model, optimal values of hyperparameters, and optimization algorithm (solver). This paper first presents a brief review of recent literature related to brain tumor classification. Secondly, a robust framework for implementing the transfer learning technique is proposed. In the proposed framework, a Cartesian product matrix is generated to determine the optimal values of the two important hyperparameters: batch size… More >

  • Open Access

    ARTICLE

    Intelligent MRI Room Design Using Visible Light Communication with Range Augmentation

    R. Priyadharsini*, A. Kunthavai

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 261-279, 2023, DOI:10.32604/iasc.2023.025884

    Abstract Radio waves and strong magnetic fields are used by Magnetic Resonance Imaging (MRI) scanners to detect tumours, wounds and visualize detailed images of the human body. Wi-Fi and other medical devices placed in the MRI procedure room produces RF noise in MRI Images. The RF noise is the result of electromagnetic emissions produced by Wi-Fi and other medical devices that interfere with the operation of the MRI scanner. Existing techniques for RF noise mitigation involve RF shielding techniques which induce eddy currents that affect the MRI image quality. RF shielding techniques are complex and lead… More >

Displaying 11-20 on page 2 of 48. Per Page