Şeref Barbaros Arik^1,2,*, İnanç Güvenç^1,2

Canadian Journal of Urology, Vol.32, No.6, pp. 569-578, 2025, DOI:10.32604/cju.2025.068094 - 30 December 2025

Abstract Objectives: Differentiating benign from malignant testicular lesions is essential to avoid unnecessary surgery and ensure timely intervention. While conventional ultrasound remains the first-line imaging method, elastography and MRI provide additional functional and structural information. This study assesses the diagnostic utility of testicular elastography and magnetic resonance imaging (MRI) in differentiating benign and malignant testicular lesions. Methods: Patients with sonographically detected testicular masses were retrospectively evaluated using elastography, scrotal MRI, and tumor markers. Quantitative and qualitative imaging findings, lesion size, and laboratory values were recorded. Statistical analyses included Fisher’s exact test, logistic regression, Receiver operating characteristic… More >

Sarfaraz Abdul Sattar Natha^1,*, Mohammad Siraj^2,*, Majid Altamimi², Adamali Shah², Maqsood Mahmud³

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4179-4201, 2025, DOI:10.32604/cmes.2025.072529 - 23 December 2025

Abstract A brain tumor is a disease in which abnormal cells form a tumor in the brain. They are rare and can take many forms, making them difficult to treat, and the survival rate of affected patients is low. Magnetic resonance imaging (MRI) is a crucial tool for diagnosing and localizing brain tumors. However, the manual interpretation of MRI images is tedious and prone to error. As artificial intelligence advances rapidly, DL techniques are increasingly used in medical imaging to accurately detect and diagnose brain tumors. In this study, we introduce a deep convolutional neural network… More >

Jingcheng Lyu^1,2,#, Ruiyu Yue^1,2,#, Boyu Yang^1,2, Xuanhao Li^1,2, Jian Song^1,2,*

Canadian Journal of Urology, Vol.32, No.5, pp. 445-456, 2025, DOI:10.32604/cju.2025.068853 - 30 October 2025

Abstract Objectives: This study aimed to develop an artificial intelligence (AI)-based image recognition system using the nnU-Net adaptive neural network to assist clinicians in detecting magnetic resonance imaging (MRI)-invisible prostate cancer. The motivation stems from the diagnostic challenges, especially when MRI findings are inconclusive (Prostate Imaging Reporting and Data System [PI-RADS] score ≤ 3). Methods: We retrospectively included 150 patients who underwent systematic prostate biopsy at Beijing Friendship Hospital between January 2013 and January 2023. All were pathologically confirmed to have clinically significant prostate cancer, despite negative findings on preoperative MRI. A total of 1475 MRI… More >

Zhenyu Li¹, Hongze Li², Jinshui Yang², Hong Hu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.010548

Abstract The urgent need to achieve "carbon neutrality" drives the development of innovative porous structures that integrate both acoustic and mechanical properties, aimed at reducing energy consumption. However, enhancing these functionalities often results in increased structural weight, which can restrict their application in scenarios where weight is a critical factor. In response to this challenge, we present a groundbreaking structural design that combines carbon fiber reinforced polymer (CFRP) composites with mechanical and acoustic metamaterials for the first time. This novel construction is characterized by its lightweight nature while delivering exceptional mechanical strength and acoustic performance.
The experimental… More >

Yibin Mao¹, Dianlong Yu^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.012290

Abstract In modern engineering, situations that require vibration reduction often come with specific pressure requirements. Mechanical metamaterials have the advantages in mechanical loading and low-frequency band gap vibration reduction. To ensure that the structure has a wide and low-frequency band gap while having a pressure resistance, a two-dimensional triangular concave negative Poisson's ratio structure with strong pressure resistance is introduced. The internal structure is designed according to the principle of local resonance. The band structure and intrinsic modes of the two-dimensional triangular concave model are calculated by the finite element method through simulation software. The band… More >

Jialong Jiao¹, Mengyun Jiang¹, Hang Xie^2,3,*, Yuanming Chen¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.9, pp. 2075-2100, 2025, DOI:10.32604/fdmp.2025.069064 - 30 September 2025

Abstract The growing demand for ocean space has generated significant interest in multi-body floating systems, where gap resonance in confined regions plays a critical role in ensuring the safety of offshore operations. This study develops a numerical tank model using the Smoothed Particle Hydrodynamics (SPH) method, implemented through the open-source code DualSPHysics, to investigate hydrodynamic resonance in a twin-floater system and to examine the influence of internal tank sloshing on its hydrodynamic characteristics. The hydrodynamic behavior of the gap flow between a fixed twin-floater system in the numerical tank is validated through systematic comparison with experimental… More >

Khalil Ibrahim Lairedj¹, Zouaoui Chama¹, Amina Bagdaoui¹, Samia Larguech², Younes Menni^3,4,*, Nidhal Becheikh⁵, Lioua Kolsi^6,*, Badr M. Alshammari⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2419-2443, 2025, DOI:10.32604/cmes.2025.069396 - 31 August 2025

Abstract Brain tumor segmentation from Magnetic Resonance Imaging (MRI) supports neurologists and radiologists in analyzing tumors and developing personalized treatment plans, making it a crucial yet challenging task. Supervised models such as 3D U-Net perform well in this domain, but their accuracy significantly improves with appropriate preprocessing. This paper demonstrates the effectiveness of preprocessing in brain tumor segmentation by applying a pre-segmentation step based on the Generalized Gaussian Mixture Model (GGMM) to T1 contrast-enhanced MRI scans from the BraTS 2020 dataset. The Expectation-Maximization (EM) algorithm is employed to estimate parameters for four tissue classes, generating a More >

Rachana Poongodan¹, Dayanand Lal Narayan², Deepika Gadakatte Lokeshwarappa³, Hirald Dwaraka Praveena⁴, Dae-Ki Kang^5,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5751-5772, 2025, DOI:10.32604/cmc.2025.066314 - 30 July 2025

Abstract In recent decades, brain tumors have emerged as a serious neurological disorder that often leads to death. Hence, Brain Tumor Segmentation (BTS) is significant to enable the visualization, classification, and delineation of tumor regions in Magnetic Resonance Imaging (MRI). However, BTS remains a challenging task because of noise, non-uniform object texture, diverse image content and clustered objects. To address these challenges, a novel model is implemented in this research. The key objective of this research is to improve segmentation accuracy and generalization in BTS by incorporating Switchable Normalization into Faster R-CNN, which effectively captures the… More >

Ovidijus Grigas, Robertas Damaševičius^*, Rytis Maskeliūnas

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1805-1838, 2025, DOI:10.32604/cmc.2025.064354 - 09 June 2025

Abstract Brain imaging is important in detecting Mild Cognitive Impairment (MCI) and related dementias. Magnetic Resonance Imaging (MRI) provides structural insights, while Positron Emission Tomography (PET) evaluates metabolic activity, aiding in the identification of dementia-related pathologies. This study integrates multiple data modalities—T1-weighted MRI, Pittsburgh Compound B (PiB) PET scans, cognitive assessments such as Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR) and Functional Activities Questionnaire (FAQ), blood pressure parameters, and demographic data—to improve MCI detection. The proposed improved Convolutional Mixer architecture, incorporating B-cos modules, multi-head self-attention, and a custom classifier, achieves a classification accuracy of 96.3% More >

Jacob PL Ho¹, Carol WK Ng², Wilfred HS Wong³, Yiu-fai Cheung^1,3,*

Congenital Heart Disease, Vol.20, No.2, pp. 201-211, 2025, DOI:10.32604/chd.2025.063217 - 30 April 2025

Abstract Background: The role of cardiothoracic ratio (CTR) from the chest radiograph for assessment of ventricular enlargement and function in repaired tetralogy of Fallot (TOF) is conflicting. This study aimed to determine the associations between CTR and cardiac magnetic resonance (CMR)-derived ventricular volumes and indices of ventricular function in adolescents and young adults with repaired TOF. Methods: The CTR and CMR findings, performed within 12 months of each other, were reviewed in 76 patients aged 22.1 ± 6.4 years. Associations between CTR and CMR parameters including right (RV) and left ventricular (LV) volumes and ejection fraction were… More >