Latest Research in Computer Vision and Pattern Recognition
20 research papers · 2026 median publication year
Top Research Topics in Computer Vision and Pattern Recognition
- Computer Vision and Pattern Recognition — 4 papers
- AI in cancer detection — 2 papers
- Ultrasound Imaging and Elastography — 2 papers
- COVID-19 diagnosis using AI — 1 papers
- Radiation Dose and Imaging — 1 papers
- Advanced X-ray and CT Imaging — 1 papers
- Hepatocellular Carcinoma Treatment and Prognosis — 1 papers
- Advanced Neural Network Applications — 1 papers
- Radiomics and Machine Learning in Medical Imaging — 1 papers
- Maternal and fetal healthcare — 1 papers
Highest-Cited Papers
- Seeing Abnormal from Normal: Glomerular Abnormality in Representations of Normal Renal Morphology
- A Voxel-Spacing-Aware Extension of PyRadiomics for Anisotropic Texture Analysis
- CirrGuide: A Deep Cascaded Framework for Liver Cirrhosis Segmentation and Severity Classification from T2-Weighted MRI
- Artificial Intelligence in Medical Imaging: A Review of Radiodiagnosis in Indian Perspectives
- Evaluation of deep-learning iterative reconstruction combined with high-frequency kernels in CT: a task-based image quality study
- KPIs-RSFNet: a deep learning-based method for glomerulus segmentation
- Clinical feasibility and image quality assessment of deep learning-based virtual contrast enhancement from photon-counting computed tomography
- CLAUNet-LFB0-CBAM a deep learning framework for explainable liver fibrosis stage classification from ultrasound images
- Hybrid Fusion of Time–Intensity Curve, Deep Learning, and Fractional Zernike–Caputo Features for Accurate Liver Lesion Classification in DCE-MRI
- AI-Augmented Ultrasound Imaging Fused with Virtual Reality 3D Reconstruction for Early-Stage Tumor Detection and Clinical Decision Support
- AI-Augmented Ultrasound Imaging Fused with Virtual Reality 3D Reconstruction for Early-Stage Tumor Detection and Clinical Decision Support
- PIEGUNet: A Physics-Inspired U-Net for Kidney MRI Segmentation in Chronic Kidney Disease
- Deep Learning Image Reconstruction Algorithm for Quantitative Assessment of Low-Dose Biphasic Chest CT in Chronic Obstructive Pulmonary Disease
- Multi-source Medical Sensor Data Fusion Using Transformer for Preoperative Assessment of Placenta Accreta Spectrum
- LiteRenalNet: A lightweight dual-branch network with channel–spatial co-attention for interpretable kidney CT classification
- Performance uncertainty in medical image analysis: a large-scale investigation of confidence intervals
- Task‐based evaluation of axial and multiplanar reconstructions in computed tomography: A volumetric analysis of spatial resolution, noise, and detectability
- FRAC-MAS: A Safe and Explainable Multi-Agent System for Fracture Diagnosis
- P1.245. Real-Time AI-Based Thoracic Duct Recognition During Thoracoscopic Esophagectomy
- P1.141. A Machine Learning Model for Assessment of Conduit Perfusion in Robotic Assisted Minimally Invasive Esophagectomy Using Indocyanine Green