Papers Fracture detection
“Fracture detection” 태그가 달린 논문 52편 · 필터 해제
RibAssist 3D: Biplanar Rib-Fracture Detection, Addressing, and Selective 3D Localization from CT-Derived Projections
Rib fractures are common and time-consuming to localize on computed tomography (CT). We ask whether fractures detected independently in two orthogonal CT-derived projections (anteroposterior and lateral) can be paired ac…
Fracture detectionRobust Cross-Domain Generalization Using Unlabeled Target Data with Source-Domain Supervision
It is often desirable to generalize medical imaging AI models trained with dense annotations to data acquired from different ultrasound scanners or clinical sites; however, retraining these models with new annotations is…
Domain GeneralizationContrastive LearningFederated LearningFracture detectionA generalizable large-scale foundation model for musculoskeletal radiographs
Artificial intelligence (AI) has shown promise in detecting and characterizing musculoskeletal diseases from radiographs. However, most existing models remain task-specific, annotation-dependent, and limited in generaliz…
Self-Supervised LearningFracture detectionEnhanced Fracture Diagnosis Based on Critical Regional and Scale Aware in YOLO
Fracture detection plays a critical role in medical imaging analysis, traditional fracture diagnosis relies on visual assessment by experienced physicians, however the speed and accuracy of this approach are constrained …
Fracture detectionFracDetNet: Advanced Fracture Detection via Dual-Focus Attention and Multi-scale Calibration in Medical X-ray Imaging
In this paper, an advanced fracture detection framework, FracDetNet, is proposed to address challenges in medical imaging, as accurate fracture detection is essential for enhancing diagnostic efficiency in clinical pract…
Fracture detectionInvisible Yet Detected: PelFANet with Attention-Guided Anatomical Fusion for Pelvic Fracture Diagnosis
Pelvic fractures pose significant diagnostic challenges, particularly in cases where fracture signs are subtle or invisible on standard radiographs. To address this, we introduce PelFANet, a dual-stream attention network…
Fracture detectionFracture Detection In X-rays Using Custom Convolutional Neural Network (CNN) And Transfer Learning Models
Bone fractures present a major global health challenge, often resulting in pain, reduced mobility, and productivity loss, particularly in low-resource settings where access to expert radiology services is limited. Conven…
Fracture detectionTransfer LearningFracture Detection and Localisation in Wrist and Hand Radiographs using Detection Transformer Variants
Background: Accurate diagnosis of wrist and hand fractures using radiographs is essential in emergency care, but manual interpretation is slow and prone to errors. Transformer-based models show promise in improving medic…
Contrastive LearningFracture detectionObject DetectionA Modified VGG19-Based Framework for Accurate and Interpretable Real-Time Bone Fracture Detection
Early and accurate detection of the bone fracture is paramount to initiating treatment as early as possible and avoiding any delay in patient treatment and outcomes. Interpretation of X-ray image is a time consuming and …
Fracture detectionDecision MakingEdge DetectionOrthoInsight: Rib Fracture Diagnosis and Report Generation Based on Multi-Modal Large Models
The growing volume of medical imaging data has increased the need for automated diagnostic tools, especially for musculoskeletal injuries like rib fractures, commonly detected via CT scans. Manual interpretation is time-…
Fracture detectionA Deep Learning-Based Ensemble System for Automated Shoulder Fracture Detection in Clinical Radiographs
Background: Shoulder fractures are often underdiagnosed, especially in emergency and high-volume clinical settings. Studies report up to 10% of such fractures may be missed by radiologists. AI-driven tools offer a scalab…
Fracture detectionPre-trained Under Noise: A Framework for Robust Bone Fracture Detection in Medical Imaging
Medical Imagings are considered one of the crucial diagnostic tools for different bones-related diseases, especially bones fractures. This paper investigates the robustness of pre-trained deep learning models for classif…
Fracture detectionTransfer LearningSelf-Supervised Multiview Xray Matching
Accurate interpretation of multi-view radiographs is crucial for diagnosing fractures, muscular injuries, and other anomalies. While significant advances have been made in AI-based analysis of single images, current meth…
Fracture detectionSecure Diagnostics: Adversarial Robustness Meets Clinical Interpretability
Deep neural networks for medical image classification often fail to generalize consistently in clinical practice due to violations of the i.i.d. assumption and opaque decision-making. This paper examines interpretability…
Adversarial AttackAdversarial RobustnessDecision MakingFracture detection+3Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays
Computer-aided diagnosis (CAD) systems have greatly improved the interpretation of medical images by radiologists and surgeons. However, current CAD systems for fracture detection in X-ray images primarily rely on large,…
Fracture detectionGPUA Comparative Study of Multiple Deep Learning Algorithms for Efficient Localization of Bone Joints in the Upper Limbs of Human Body
This paper addresses the medical imaging problem of joint detection in the upper limbs, viz. elbow, shoulder, wrist and finger joints. Localization of joints from X-Ray and Computerized Tomography (CT) scans is an essent…
Fracture detectionA novel approach towards the classification of Bone Fracture from Musculoskeletal Radiography images using Attention Based Transfer Learning
Computer-aided diagnosis (CAD) is today considered a vital tool in the field of biological image categorization, segmentation, and other related tasks. The current breakthrough in computer vision algorithms and deep lear…
Fracture detectionImage CategorizationMedical Image AnalysisTransfer LearningPediatric Wrist Fracture Detection Using Feature Context Excitation Modules in X-ray Images
Children often suffer wrist trauma in daily life, while they usually need radiologists to analyze and interpret X-ray images before surgical treatment by surgeons. The development of deep learning has enabled neural netw…
2D Object DetectionFracture detectionmedical image detectionobject-detection+2YOLOv8-ResCBAM: YOLOv8 Based on An Effective Attention Module for Pediatric Wrist Fracture Detection
Wrist trauma and even fractures occur frequently in daily life, particularly among children who account for a significant proportion of fracture cases. Before performing surgery, surgeons often request patients to underg…
Fracture detectionAACLiteNet: A Lightweight Model for Detection of Fine-Grained Abdominal Aortic Calcification
Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, taking 17.9 million lives annually. Abdominal Aortic Calcification (AAC) is an established marker for CVD, which can be observed in lateral view Ve…
Fracture detection