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107 articles for “CT”
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CTCHFA: Discovery of Circulating Tumor Cells in Metastatic Breast Cancer and Nonmetastatic Cancer by using Novel Hybrid Hierarchical Clustering Algorithm in Firefly Distance
Abstract: AbstractBlood testing for circulating tumor cells (CTCs) has emerged as one of the highest fields in cancer research. CTC detection are an early gene marker of reaction to systemic therapy, whereas their molecular characterization has a strong field that can be translated to individualized targeted treatments and spare breast cancer (BC) patients from unnecessary and ineffective therapies. Genomic research regarding CTCs monitoring for BC is limited due to the lack …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 1, 2015 · pp. 9–18 Read article
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Gold Nanoparticle Size, Biodistribution, and Toxicity: Insights from DualEnergy CT
Abstract: Dual-energy and spectral computed tomography (CT) have emerged as powerful platforms for noninvasive, quantitative mapping of nanoparticle biodistribution in vivo. By exploiting the energy-dependent attenuation profiles of high-atomic-number (high-Z) materials, these systems enable material decomposition and element-specific imaging, thereby distinguishing nanoparticle signals from those of soft tissues and conventional iodinated contrast agents. Photon-counting spectral CT further enhances this capability by binning individual photons into multiple energy channels, improving spatial resolution, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 · pp. 22–34 Read article
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Fusion of CT and MRI Scanned Medical Images Using Image Processing
Abstract: ABSTRACTIn the field of medicine, to evaluate or to examine the inner body parts, different radiometric scanning techniques can be used. Some most commonly used scanning techniques include the computerized tomography (CT) scan and magnetic resonance imaging (MRI) scan but the images of various body parts taken by using these scanning techniques have their own merits and demerits. MRI scans can show the images of soft tissues very clearly but …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 3, 2012 · pp. 17–20 Read article
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Estimation of Splenic Volume: Prolate Ellipsoid Method Correlated with 3-D Helical CT Determination
Abstract: To establish the correlation between two methods of volume estimation of spleen, e.g., prolate ellipsoid formula and 3-D reconstruction of abdominal helical CT-image. Settings and Design: One hundred twenty-six patients were selected aged between 20 and 80 years in which male and female were 72 and 54 respectively for cross-sectional study. Patients who had underlying malignancy, infections, hematological disorders and other conditions that could alter splenic size were excluded. Methods …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 1, Issue 1, 2012 · pp. 28–33 Read article
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Nano‑Enabled CT for Cancer Imaging: From Molecular Targeting to Image‑Guided Therapy
Abstract: Nano‑enabled computed tomography (CT) exploits high‑atomic‑number (high‑Z) nanomaterials engineered with targeting ligands and therapeutic payloads to enhance contrast, enable molecular imaging, and support image‑guided interventions in oncology. Tumor‑specific nanoprobes such as RGD‑modified gold nanorods, polymer‑coated bismuth nanoparticles, and peptide, antibody, or aptamer‑functionalized platforms can intensify tumor conspicuity, allow early lesion detection and staging, and provide real‑time treatment monitoring. Integration of CT visibility with photothermal, photodynamic, chemo‑, radio‑, and immunotherapeutic functions …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 40–49 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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A Comprehensive Review on Nanostructured Polymer Composites for CT Imaging Contrast Enhancement in Brain Tumor Diagnosis
Abstract: The detection and characterization of brain tumors require high-resolution and non-invasive imaging modalities that have the ability of differentiating tumorous tissues and healthy brain tissues. Computed tomography (CT) can be included in this number because, in addition to providing speedy scans and penetration to deep tissue, the diagnostic capability in soft tissue organ such as the brain is poor despite low natural contrast. The review is dedicated to the emerging …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 148–162 Read article
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Integration of Nano Ct and SEM in Study of Marcellus Shale Heterogeneity
Abstract: The increase in exploration and production in shale gas reservoir, and few studies so far reported regarding the general topology of tight reservoir, it is now imperative to critically understand the complexities surrounding the geology of shale reservoirs and its characterization. To understand the transport processes in any shale medium, we need to enhance our knowledge of the geometry and topology of the tight shale rock. The Marcellus Shale has …
Published in Journal of Petroleum Engineering & Technology · Vol. 5, Issue 3, 2015 · pp. 39–51 Read article
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Analysis of Discrete Wavelet Transform for Denoising of Breast CT Image
Abstract: During acquisition of medical images noise gets induced in the digital image by various effects. The state of art devices used for capturing the images introduces complex type of addition noise in the images. No medical imaging devices are noise free. The most commonly used medical images are acquired from MRI (Magnetic Resonance Imaging), CT (Computed Tomography) and X-ray equipment’s. Additive noise into medical image decreases the visual quality that …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 1, 2018 · pp. 27–31 Read article
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Human Deep Skin Surface Vibration Frequency Detection from CT and DT Signals Using Genetic Algorithms
Abstract: To diagnose respiratory problems early on, a contactless, non-invasive, real-time assessment of human vibration is a crucial prerequisite. Optoelectronic plethysmography (OEP) and the forced oscillation technique (FOT), are two widely utilized methodologies, depending on variations in each patient’s local chest impedance. Calibration of the devices before each measurement is hence the primary problem of these approaches. This report presents a simulation-based analysis to assess the effectiveness of the CT and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 9–16 Read article
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Study of Performance of Photoelectrochemical Cell for Solar Energy Conversion and Storage in Carbol Fuchsin-CTAB-EDTA System
Abstract: Power storage capacity is becoming more necessary as wind and solar power sources rapidly enter the commercial market. The Photoelectrochemical Cell as they are described in the current manuscript are promising energy technologies since they allow for the generation and storage of solar energy. In addition to the requirement for power storage, photoelectrochemical Cell (PEC) are particularly important because these solar devices can produce and store solar power simultaneously. Photoelectrochemical …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 14, Issue 1, 2024 · pp. 47–55 Read article
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Detection and Classification of Brain Tumor from MRI And CT Images using Harmony Search Optimization and Deep Learning
Abstract: Primary brain tumor detection and classification are critical factors in ensuring effective treatment and, ultimately, improving patient well-being. This paper describes a novel method for detecting and classifying brain tumors with the help of magnetic resonance imaging (MRI) and computed tomography (CT) images. The suggested method combines harmony search optimization (HSO) and Convolution Neural Networks (CNN) based on deep learning techniques, yielding an impressive accuracy rate of 99.13% for both …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 31–49 Read article
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Utilizing circulation-derived cancer cells to evaluate patients with surgically treated stages I–IIIA NSCLC throughout the preoperative phase
Abstract: Context: When a tumor is considered resectable, surgery is viewed as the primary treatment approach for both early-stage and locally advanced non-small cell lung cancer (NSCLC). One of the most exciting areas of cancer research in the past ten years is liquid biopsy, which offers a practical non-invasive method for cancer detection and tracking. Circulating tumor cells (CTCs) have been linked to a worse prognosis and increased chance of relapse …
Published in Research and Reviews : Journal of Surgery · Vol. 13, Issue 3, 2024 · pp. 17–28 Read article
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Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.
Abstract: Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 13–21 Read article
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The Critical Role of Cyber Threat Intelligence in Countering Terrorism: Challenges, Successes and Policy Recommendations
Abstract: Cyber threats from terrorist organizations pose severe risks to national security, economic stability and public safety. Cyber threat intelligence (CTI) has emerged as a crucial capability for pre-empting and disrupting cyberterrorism attempts through systematic monitoring of threat actors, along with analytical frameworks to contextualize tradecraft. This paper provides an extensive overview of CTI, analyzing the state of the art of intelligence gathering frameworks against threat groups by assessing technologies like …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 22–29 Read article
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Managing Carpal Tunnel Syndrome: Insights into Symptoms and Relief
Abstract: Carpal tunnel syndrome (CTS) is a prevalent and concerning issue affecting the wrist and hand, arising from the compression of the median nerve within the carpal tunnel. This compression results in a spectrum of distressing symptoms, including numbness, tingling, weakness, and discomfort, particularly in the thumb, index, and middle fingers. Despite its frequent association with repetitive hand movements and prolonged use of computers or handheld devices, CTS can stem from …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 1, Issue 2, 2023 · pp. 6–12 Read article
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Thermo-Mechanical Behavior and Intelligent Optimization of Contact Temperature During Ultrasonic Vibration-Assisted Single-Pole Magnetic Abrasive Finishing of Zinc Alloy
Abstract: This study proposes a new integration of the experimental analysis, multi-physics finite element modelling (FEM) and machine learning (ML) optimisation of contact temperature (CT) in ultrasonic vibration-assisted single pole magnetic abrasive finishing (UV-SPMAF) of zinc alloy. The three gaps of the research are addressed: (i) The absence of a multi-physics FEM model that can couple electromagnetic, thermal and structural fields for UV-SPMAF of zinc; (ii) No quantified contribution of the …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 2, 2026 Read article
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The Evolution of Bio Crypt Keys: From Concept to Implementation
Abstract: With the rapid increase in data exfiltration due to cyber-attacks, Covert Timing Channels (CTCs) have emerged as a significant and sophisticated network security threat. These channels exploit inter-arrival times of data packets to exfiltrate sensitive information from targeted networks. Detecting CTCs increasingly relies on machine learning techniques, which use statistical metrics to differentiate between malicious (covert) and legitimate (overt) traffic flows. However, as cyber-attacks become more adept at evading detection …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 38–45 Read article
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Characterization of Mechanical and Viscoelastic Properties of Ceramic Nanoparticle-Reinforced Polymer Composites
Abstract: This study examines the mechanical and viscoelastic properties of polymer composites reinforced with ceramic nanoparticles, specifically focusing on enhancing the performance of the material through the incorporation of alumina nanoparticles. The composites were produced by embedding alumina nanoparticles into an epoxy matrix, and their properties were assessed using tensile, flexural, and dynamic mechanical analyses (DMA). The tensile tests showed a remarkable 40% increase in tensile strength and a 35% enhancement …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 71–82 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article