FERDINANDO CALABRIA¹, ANTONIO BAGNATO¹, GIULIANA GUADAGNINO², MARIA TOTEDA¹, ANTONIO LANZILLOTTA¹, STEFANIA CARDEI¹, ROSANNA TAVOLARO¹, MARIO LEPORACE^1,*

Oncology Research, Vol.31, No.2, pp. 117-124, 2023, DOI:10.32604/or.2023.027705

Abstract We observed several patients presenting 2-[¹⁸F]FDG uptake in the reactive axillary lymph node at PET/CT imaging, ipsilateral to the site of the COVID-19 vaccine injection. Analog finding was documented at [¹⁸F]Choline PET/CT. The aim of our study was to describe this source of false positive cases. All patients examined by PET/CT were included in the study. Data concerning patient anamnesis, laterality, and time interval from recent COVID-19 vaccination were recorded. SUVmax was measured in all lymph nodes expressing tracer uptake after vaccination. Among 712 PET/CT scans with 2-[¹⁸F]FDG, 104 were submitted to vaccination; 89/104 patients (85%) presented axillary and/or deltoid… More >

Muhammad Tahir^1,*, Farhan Riaz², Imran Usman^1,3, Mohamed Ibrahim Habib¹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 4007-4022, 2023, DOI:10.32604/csse.2023.032359

Abstract The identification of cancer tissues in Gastroenterology imaging poses novel challenges to the computer vision community in designing generic decision support systems. This generic nature demands the image descriptors to be invariant to illumination gradients, scaling, homogeneous illumination, and rotation. In this article, we devise a novel feature extraction methodology, which explores the effectiveness of Gabor filters coupled with Block Local Binary Patterns in designing such descriptors. We effectively exploit the illumination invariance properties of Block Local Binary Patterns and the inherent capability of convolutional neural networks to construct novel rotation, scale and illumination invariant features. The invariance characteristics of… More >

Sarkar Hasan Ahmed¹, Adel Al-Zebari², Rizgar R. Zebari³, Subhi R. M. Zeebaree^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3993-4008, 2023, DOI:10.32604/cmc.2023.037464

Abstract Remote sensing (RS) presents laser scanning measurements, aerial photos, and high-resolution satellite images, which are utilized for extracting a range of traffic-related and road-related features. RS has a weakness, such as traffic fluctuations on small time scales that could distort the accuracy of predicted road and traffic features. This article introduces an Optimal Deep Learning for Traffic Critical Prediction Model on High-Resolution Remote Sensing Images (ODLTCP-HRRSI) to resolve these issues. The presented ODLTCP-HRRSI technique majorly aims to forecast the critical traffic in smart cities. To attain this, the presented ODLTCP-HRRSI model performs two major processes. At the initial stage, the… More >

Mohammed Jasim Mohammed Jasim¹, Bzar Khidir Hussan², Subhi R. M. Zeebaree^3,*, Zainab Salih Ageed⁴

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3677-3693, 2023, DOI:10.32604/cmc.2023.037363

Abstract The major mortality factor relevant to the intestinal tract is the growth of tumorous cells (polyps) in various parts. More specifically, colonic polyps have a high rate and are recognized as a precursor of colon cancer growth. Endoscopy is the conventional technique for detecting colon polyps, and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss rate. The automated diagnosis of polyps in a computer-aided diagnosis (CAD) method is implemented using statistical analysis. Nowadays, Deep Learning, particularly through Convolution Neural networks… More >

Peiren Wang^1,*, Jinqiang Bi¹, Zilong Li¹, Xue Han¹, Zhengyang Li², Xiaozheng Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3197-3211, 2023, DOI:10.32604/cmes.2023.024305

Abstract Tabletop integral imaging display with a more realistic and immersive experience has always been a hot spot in three-dimensional imaging technology, widely used in biomedical imaging and visualization to enhance medical diagnosis. However, the traditional structural characteristics of integral imaging display inevitably introduce the flipping effect outside the effective viewing angle. Here, a full-parallax tabletop integral imaging display without the flipping effect based on space-multiplexed voxel screen and compound lens array is demonstrated, and two holographic functional screens with different parameters are optically designed and fabricated. To eliminate the flipping effect in the reconstruction process, the space-multiplexed voxel screen consisting… More > Graphic Abstract

Emna Karray¹, Hela Elmannai^2,*, Elyes Toumi¹, Mohamed Hedi Gharbia³, Souham Meshoul², Hamouda Aichi⁴, Zouhaier Ben Rabah¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1399-1425, 2023, DOI:10.32604/cmes.2023.023164

Abstract Pedo-spectroscopy has the potential to provide valuable information about soil physical, chemical, and biological properties. Nowadays, we may predict soil properties using VNIR field imaging spectra (IS) such as Prisma satellite data or laboratory spectra (LS). The primary goal of this study is to investigate machine learning models namely Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) for the prediction of several soil properties, including clay, sand, silt, organic matter, nitrate NO3-, and calcium carbonate CaCO3, using five VNIR spectra dataset combinations (% IS, % LS) as follows: C1 (0% IS, 100% LS), C2 (20% IS, 80% LS),… More > Graphic Abstract

Wazir Muhammad¹, Zuhaibuddin Bhutto^2,*, Salman Masroor^3,4, Murtaza Hussain Shaikh⁵, Jalal Shah², Ayaz Hussain¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1121-1142, 2023, DOI:10.32604/cmes.2023.021438

Abstract Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues. These challenges are increasing the interest in the quality of medical images. Recent research has proven that the rapid progress in convolutional neural networks (CNNs) has achieved superior performance in the area of medical image super-resolution. However, the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance (MR) images, adding extra noise in the models and more memory consumption. Furthermore, conventional deep CNN approaches used layers in series-wise connection to create the deeper mode, because this later end layer cannot… More >

Ali F. Khalifa¹, Eman Badr^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1995-2024, 2023, DOI:10.32604/cmc.2023.035888

Abstract Image segmentation is crucial for various research areas. Many computer vision applications depend on segmenting images to understand the scene, such as autonomous driving, surveillance systems, robotics, and medical imaging. With the recent advances in deep learning (DL) and its confounding results in image segmentation, more attention has been drawn to its use in medical image segmentation. This article introduces a survey of the state-of-the-art deep convolution neural network (CNN) models and mechanisms utilized in image segmentation. First, segmentation models are categorized based on their model architecture and primary working principle. Then, CNN categories are described, and various models are… More >

Mohd Aminudin Jamlos^1,*, Nur Amirah Othman¹, Wan Azani Mustafa², Mohd Faizal Jamlos³, Mohamad Nur Khairul Hafizi Rohani²

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 277-292, 2023, DOI:10.32604/cmc.2023.032840

Abstract Metamaterials (MTM) can enhance the properties of microwaves and also exceed some limitations of devices used in technical practice. Note that the antenna is the element for realizing a microwave imaging (MWI) system since it is where signal transmission and absorption occur. Ultra-Wideband (UWB) antenna superstrates with MTM elements to ensure the signal transmitted from the antenna reaches the tumor and is absorbed by the same antenna. The lack of conventional head imaging techniques, for instance, Magnetic Resonance Imaging (MRI) and Computerized Tomography (CT)-scan, has been demonstrated in the paper focusing on the point of failure of these techniques for… More >

Debnath Bhattacharyya¹, Eali. Stephen Neal Joshua², N. Thirupathi Rao², Yung-cheol Byun^3,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1447-1465, 2023, DOI:10.32604/cmc.2023.031878

Abstract Lung cancer is the leading cause of mortality in the world affecting both men and women equally. When a radiologist just focuses on the patient’s body, it increases the amount of strain on the radiologist and the likelihood of missing pathological information such as abnormalities are increased. One of the primary objectives of this research work is to develop computer-assisted diagnosis and detection of lung cancer. It also intends to make it easier for radiologists to identify and diagnose lung cancer accurately. The proposed strategy which was based on a unique image feature, took into consideration the spatial interaction of… More >