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Suggested Topics within your search.
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3461
Transformative insights in breast cancer: review of atomic force microscopy applications
Published 2025-02-01“…This review explores recent advancements in AFM technology as applied to breast cancer research, emphasizing key findings that include the differentiation of various stages of tumor progression through high-resolution imaging, precise characterization of mechanical properties, and the capability for single-cell analysis. …”
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3462
Study on the influence of horizontal stress difference coefficient on hydraulic fracturing fracture
Published 2025-04-01“…The fractal dimension was calculated by binarization of hydraulic fracture images. The analysis results show that when the horizontal stress difference coefficient is large, the fracture direction is controlled by the maximum horizontal principal stress, and it is easier to form a single through crack, while when the horizontal stress difference coefficient is low, the control effect of the maximum principal stress is weakened, the range of micro-cracks will be expanded, and the hydraulic fracture complexity is relatively higher.…”
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3463
Challenges in Distinguishing Neuro-Behcets Disease from Other Neurological Conditions. A case report from Pakistan
Published 2025-04-01“…Cerebrospinal fluid analysis showed elevated protein levels and neutrophils, consistent with NBD. …”
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3464
Mitochondria-tropic radioconjugates to enhance the therapeutic potential of terbium-161
Published 2025-04-01“…In vivo studies were conducted using SCID/Beige mice bearing PCa xenografts and involved µSPECT/CT imaging and radiometabolite analysis to evaluate biodistribution, pharmacokinetics, tumor uptake and in vivo stability of the radiocomplexes. …”
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3465
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3466
Factors Associated with Longitudinal Changes in Mammographic Density in a Multiethnic Breast Screening Cohort of Postmenopausal Women
Published 2023-01-01“…Our findings support the complexity of the relationships between breast density, BMI, hormone exposure, and breast cancer risk.…”
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3467
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3468
Three-dimensional reconstruction cloud studio based on semi-supervised generative adversarial networks
Published 2019-03-01“…Because of the intrinsic complexity in computation,three-dimensional (3D) reconstruction is an essential and challenging topic in computer vision research and applications.The existing methods for 3D reconstruction often produce holes,distortions and obscure parts in the reconstructed 3D models.While the 3D reconstruction algorithms based on machine learning can only reconstruct voxelized 3D models for simple isolated objects,they are not adequate for real usage.From 2014,the generative adversarial network (GAN) is widely used in generating unreal dataset and semi-supervised learning.So the focus of this paper is to achieve high quality 3D reconstruction performance by adopting GAN principle.A novel semi-supervised 3D reconstruction framework,namely SS-GAN-3D was proposed,which can iteratively improve any raw 3D reconstruction models by training the GAN models to converge.This new model only takes 2D observation images as the weak supervision,and doesn’t rely on prior knowledge of shape models or any referenced observations.Finally,through qualitative and quantitative experiments and analysis,this new method shows compelling advantages over the current state-of-the-art methods on Tanks & Temples and ETH3D reconstruction benchmark datasets.Based on SS-GAN-3D,the 3D reconstruction studio solution was proposed.…”
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3469
Hybrid transformer-CNN and LSTM model for lung disease segmentation and classification
Published 2024-12-01“…The improved accuracy achieved by the L-MLSTM model highlights its capability to better handle the complexity and variability in lung images. This hybrid approach enhances the model’s ability to distinguish between different types of lung diseases and reduces diagnostic errors compared to existing methods.…”
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3470
A topological approach to positron emission particle tracking for finding multiple particles in high noise environments
Published 2025-04-01“…Abstract Positron emission particle tracking (PEPT) is an advanced imaging technique that accurately tracks the three-dimensional spatial coordinates of a radioactively-labelled particle with sub-millimetre and sub-millisecond precision. …”
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3471
Empowering public participation in assessing the indicators of aesthetic value for historical landscape: a case study on Melaka, Malaysia
Published 2024-12-01“…This study aims to identify reliable indicators by testing public perception, thus resulting in nine indicators derived from aesthetic-based theories: mystery, coherence, legibility, openness, disturbance, complexity, naturalness, and diversity. We conducted an online closed-ended questionnaire survey with 126 respondents using five refined images from the historical city of Melaka, Malaysia that showcase unique urban landscape features. …”
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3472
Reliable detection of CNS lymphoma-derived circulating tumor DNA in cerebrospinal fluid using multi-biomarker NGS profiling: insights from a real-world study
Published 2025-05-01“…Abstract Background Diagnosing primary or secondary CNS lymphoma (CNSL) is a clinical challenge due to the limitations of standard biopsy and imaging procedures despite established guidelines. …”
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3473
DOF Enhanced via the Multi-Wavelength Method for the Moiré Fringe-Based Alignment
Published 2025-03-01“…The Moiré fringe-based alignment method has the advantages of high precision and low complexity. However, the precision of this method is highly sensitive to variations in the gap between the wafer and the mask. …”
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3474
Optimization of diagnostics of retinopathy of prematurity stages based on the integration of clinical data using the Key to Diagnosis I software
Published 2022-07-01“…The presence o f“mute” zones, macula localization, traction index of the macular zone (Tm), zone and span of pathological changes, fractal dimension (Df) and complexity of vascular system (СVS) were assessed on automatically created wide-field images, obtained by Ret-Cam Shuttle. …”
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3475
KSTRV1: A scene text recognition dataset for central Kurdish in (Arabic-Based) scriptZenodo
Published 2025-06-01“…Additionally, 20,000 synthetic text instances have been generated to enhance the dataset’s diversity, quantity, and quality by incorporating varied fonts, orientations, distortions, and background complexities.KSTRV1 captures the multilingual landscape of the Kurdistan Region while addressing real-world challenges like occlusion, lighting variations, and script complexity. …”
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3476
Eosinophilic Fasciitis: A Review of Research and Therapeutic Possibilities
Published 2024-12-01“…Conclusion EF is a rare disease, and its complexity, due to diverse etiologies and variable treatment efficacy, poses significant challenges in clinical practice. …”
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3477
A Compact Real-Time PCR System for Point-of-Care Detection Using a PCB-Based Disposable Chip and Open-Platform CMOS Camera
Published 2025-05-01“…The system integrates precise thermal cycling with software-synchronized fluorescence detection and provides real-time analysis through a dedicated user interface. To minimize cost and complexity, a polycarbonate reaction chamber was integrated with a PCB-based heater and thermistor. …”
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3478
Anomaly detection in cropland monitoring using multiple view vision transformer
Published 2025-04-01“…The pipeline includes the meticulous collection of a vast array of normal and abnormal farmland images, followed by preprocessing to standardize data. …”
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A rare case of a giant pulmonary solitary fibrous tumor: Diagnostic and therapeutic challenges in the absence of malignancy
Published 2025-01-01“…Discussion: This case highlights the unique diagnostic complexity of SFTs, particularly with tumors of exceptional size. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation
Published 2024-11-01“…The methodology is strategically designed to address the complexities and variations in cephalometric images through a dual learning process: building base learners using end-to-end regression approaches and then constructing a meta-learner that ensembles the output of the base models to obtain collective predictions. …”
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