A. Manju¹, R. kaladevi², Shanmugasundaram Hariharan³, Shih-Yu Chen^4,5,*, 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 images of Magnetic Resonance Imaging… More >

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 model is carried out with… More >

Mimouna Abdullah Alkhonaini¹, Siwar Ben Haj Hassine², Marwa Obayya³, Fahd N. Al-Wesabi², Anwer Mustafa Hilal^4,*, 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 fine tuning detection of tumor… More >