Hui Xu, Yalin Hu^*, Weidong Cao, Longjie Han

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3239-3255, 2023, DOI:10.32604/cmc.2023.039227

Abstract The massive influx of traffic on the Internet has made the composition of web traffic increasingly complex. Traditional port-based or protocol-based network traffic identification methods are no longer suitable for today’s complex and changing networks. Recently, machine learning has been widely applied to network traffic recognition. Still, high-dimensional features and redundant data in network traffic can lead to slow convergence problems and low identification accuracy of network traffic recognition algorithms. Taking advantage of the faster optimization-seeking capability of the jumping spider optimization algorithm (JSOA), this paper proposes a jumping spider optimization algorithm that incorporates the harris hawk optimization (HHO) and… More >

Kainat Nazir¹, Tahir Mustafa Madni¹, Uzair Iqbal Janjua¹, Umer Javed², Muhammad Attique Khan³, Usman Tariq⁴, Jae-Hyuk Cha^5,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2861-2877, 2023, DOI:10.32604/cmc.2023.039181

Abstract Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved ones. Diagnosing a brain tumor usually begins with magnetic resonance imaging (MRI). The manual brain tumor diagnosis from the MRO images always requires an expert radiologist. However, this process is time-consuming and costly. Therefore, a computerized technique is required for brain tumor detection in MRI images. Using the MRI, a novel mechanism of the three-dimensional (3D) Kronecker convolution feature pyramid (KCFP) is used to segment brain tumors, resolving the pixel loss and weak processing of multi-scale lesions. A single dilation rate was replaced… More >

Nerejda Shehu^1,*, Christian Meierhofer¹, Anja Hennemuth^2,3, Markus Hüllebrand^2,3, Pavlo Yevtushenko³, Peter Ewert¹, Stefan Martinoff⁴, Heiko Stern¹

Congenital Heart Disease, Vol.18, No.4, pp. 461-474, 2023, DOI:10.32604/chd.2023.031075

Abstract Background: Pressure measurement in total cavopulmonary connection (TCPC) patients is a domain of cardiac catheterization. 4D velocity encoded cardiovascular magnetic resonance (4D–flow MRI) offers an alternative for assessment of even minor pressure differences. The scope of this study was to measure even minor pressure differences in the anastomosis of TCPC patients, who are clinically uncompromised. Methods: Twenty-four patients (median 15 years [8;34]) with TCPC were studied prospectively by 4D-flow MRI. Pressure differences between superior vena cava (SVC) and extracardiac conduit (C) to both right pulmonary artery (RPA) and left pulmonary artery (LPA) were assessed. Small fluid obstructions as vortices within… More > Graphic Abstract

Alaa Alsaheel, Reem Alhassoun, Reema Alrashed, Noura Almatrafi, Noura Almallouhi, Saleh Albahli^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2461-2482, 2023, DOI:10.32604/cmc.2023.040257

Abstract With the increasing use of deep learning technology, there is a growing concern over creating deep fake images and videos that can potentially be used for fraud. In healthcare, manipulating medical images could lead to misdiagnosis and potentially life-threatening consequences. Therefore, the primary purpose of this study is to explore the use of deep learning algorithms to detect deep fake images by solving the problem of recognizing the handling of samples of cancer and other diseases. Therefore, this research proposes a framework that leverages state-of-the-art deep convolutional neural networks (CNN) and a large dataset of authentic and deep fake medical… More >

Abdul Haseeb¹, Muhammad Attique Khan^1,*, Faheem Shehzad¹, Majed Alhaisoni², Junaid Ali Khan¹, Taerang Kim³, Jae-Hyuk Cha³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2397-2415, 2023, DOI:10.32604/csse.2023.040529

Abstract X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost. However, the manual categorization of knee joint disorders is time-consuming, requires an expert person, and is costly. This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm. Two pre-trained deep learning models (Efficientnet-b0 and Densenet201) have been employed for the training and feature extraction. Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images. In the next step, fusion is performed using a canonical… More >

Abdul Qadir¹, Rabbia Mahum¹, Suliman Aladhadh^2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1365-1384, 2023, DOI:10.32604/csse.2023.037033

Abstract A considerable portion of the population now experiences osteoarthritis of the knee, spine, and hip due to lifestyle changes. Therefore, early treatment, recognition and prevention are essential to reduce damage; nevertheless, this time-consuming activity necessitates a variety of tests and in-depth analysis by physicians. To overcome the existing challenges in the early detection of Knee Osteoarthritis (KOA), an effective automated technique, prompt recognition, and correct categorization are required. This work suggests a method based on an improved deep learning algorithm that makes use of data from the knee images after segmentation to detect KOA and its severity using the Kellgren-Lawrence… More >

Patrick C. Doherty, Heather E. Dillon^† , Justin Roberts

Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-6, 2017, DOI:10.5098/hmt.9.1

Abstract The onset of turbulence in natural convection systems is difficult to predict using traditional computational techniques. The flow patterns that occur before and after the onset of turbulence may be better understood with the help of visual techniques like Schlieren imaging. Schlieren imaging allows visualization of the density gradients of a fluid using collimated light and refractive properties. In this experiment, a device was designed to test the behavior of airflow with non-isothermal boundary conditions within a rectangular cavity. Previous computational fluid modeling suggested a period doubling route to chaos in a cavity with a high aspect ratio and free… More >

Ingo Paetsch^1,*, Roman Gebauer², Christian Paech², Frank-Thomas Riede², Sabrina Oebel¹, Andreas Bollmann¹, Christian Stehning³, Jouke Smink⁴, Ingo Daehnert², Cosima Jahnke¹

Congenital Heart Disease, Vol.18, No.3, pp. 279-294, 2023, DOI:10.32604/chd.2023.029634

Abstract Background: In congenital heart disease (CHD) patients, detailed three-dimensional anatomy depiction plays a pivotal role for diagnosis and therapeutical decision making. Hence, the present study investigated the applicability of an advanced cardiovascular magnetic resonance (CMR) whole heart imaging approach utilizing nonselective excitation and compressed sensing for anatomical assessment and interventional guidance of CHD patients in comparison to conventional dynamic CMR angiography. Methods: 86 consecutive pediatric patients and adults with congenital heart disease (age, 1 to 74 years; mean, 35 years) underwent CMR imaging including a free-breathing, ECG-triggered 3D nonselective SSFP whole heart acquisition using compressed SENSE (nsWHcs). Anatomical assessability and… More >

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 >