Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (5)
  • Open Access

    ARTICLE

    MCIF-Transformer Mask RCNN: Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

    Huiling Lu1,*, Tao Zhou2,3

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4371-4393, 2024, DOI:10.32604/cmc.2024.047827

    Abstract The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis. However, in PET/CT (Positron Emission Tomography/Computed Tomography) lung images, the lesion shapes are complex, the edges are blurred, and the sample numbers are unbalanced. To solve these problems, this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model (MCIF-Transformer Mask RCNN) for PET/CT lung tumor instance segmentation, The main innovative works of this paper are as follows: Firstly, the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images. The pixel dependence relationship… More >

  • Open Access

    ARTICLE

    Long Noncoding RNA Urothelial Carcinoma-Associated 1 Promotes the Proliferation and Metastasis of Human Lung Tumor Cells by Regulating MicroRNA-144

    Dagang Li*, Huizong Li, Yuping Yang*, Le Kang*

    Oncology Research, Vol.26, No.4, pp. 537-546, 2018, DOI:10.3727/096504017X15009792179602

    Abstract Long noncoding RNA urothelial carcinoma-associated 1 (lncRNA UCA1) has gained more attention in recent years due to its oncogenic roles in various cancers. MicroRNA-144 (miR-144) participates in the regulation of the growth of many cancer cells. This study investigated the interaction between lncRNA UCA1 and miR-144 in lung cancer cells. The potential downstream protein of miR-144 was also assessed. Our results found that lncRNA UCA1 was highly expressed in human lung cancer A549, H517, H4006, H1299, and H1650 cells compared to normal embryonic lung WI-38 and HEL-1 cells. Knockdown of lncRNA UCA1 significantly inhibited lung More >

  • Open Access

    ARTICLE

    Early Diagnosis of Lung Tumors for Extending Patients’ Life Using Deep Neural Networks

    A. Manju1, R. kaladevi2, Shanmugasundaram Hariharan3, Shih-Yu Chen4,5,*, Vinay Kukreja6, Pradip Kumar Sharma7, Fayez Alqahtani8, Amr Tolba9, Jin Wang10

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 993-1007, 2023, DOI:10.32604/cmc.2023.039567

    Abstract The medical community has more concern on lung cancer analysis. Medical experts’ physical segmentation of lung cancers is time-consuming and needs to be automated. The research study’s objective is to diagnose lung tumors at an early stage to extend the life of humans using deep learning techniques. Computer-Aided Diagnostic (CAD) system aids in the diagnosis and shortens the time necessary to detect the tumor detected. The application of Deep Neural Networks (DNN) has also been exhibited as an excellent and effective method in classification and segmentation tasks. This research aims to separate lung cancers from… More >

  • Open Access

    ARTICLE

    Smart Lung Tumor Prediction Using Dual Graph Convolutional Neural Network

    Abdalla Alameen*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 369-383, 2023, DOI:10.32604/iasc.2023.031039

    Abstract A significant advantage of medical image processing is that it allows non-invasive exploration of internal anatomy in great detail. It is possible to create and study 3D models of anatomical structures to improve treatment outcomes, develop more effective medical devices, or arrive at a more accurate diagnosis. This paper aims to present a fused evolutionary algorithm that takes advantage of both whale optimization and bacterial foraging optimization to optimize feature extraction. The classification process was conducted with the aid of a convolutional neural network (CNN) with dual graphs. Evaluation of the performance of the fused… More >

  • Open Access

    ARTICLE

    Detection of Lung Tumor Using ASPP-Unet with Whale Optimization Algorithm

    Mimouna Abdullah Alkhonaini1, Siwar Ben Haj Hassine2, Marwa Obayya3, Fahd N. Al-Wesabi2, Anwer Mustafa Hilal4,*, Manar Ahmed Hamza4, Abdelwahed Motwakel4, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3511-3527, 2022, DOI:10.32604/cmc.2022.024583

    Abstract The unstructured growth of abnormal cells in the lung tissue creates tumor. The early detection of lung tumor helps the patients avoiding the death rate and gives better treatment. Various medical image modalities can help the physicians in the diagnosis of disease. Many research works have been proposed for the early detection of lung tumor. High computation time and misidentification of tumor are the prevailing issues. In order to overcome these issues, this paper has proposed a hybrid classifier of Atrous Spatial Pyramid Pooling (ASPP)-Unet architecture with Whale Optimization Algorithm (ASPP-Unet -WOA). To get a… More >

Displaying 1-10 on page 1 of 5. Per Page