Papers medical image detection
“medical image detection” 태그가 달린 논문 23편 · 필터 해제
Text Over Image: Auditing Multimodal Robustness in Synthetic Medical Image Detection
With the rapid adoption of generative AI, synthetic medical images pose growing risks, including diagnostic deception and insurance fraud. Although prior work has explored vision-language model (VLM)-based synthetic imag…
medical image detectionMedROV: Towards Real-Time Open-Vocabulary Detection Across Diverse Medical Imaging Modalities
Traditional object detection models in medical imaging operate within a closed-set paradigm, limiting their ability to detect objects of novel labels. Open-vocabulary object detection (OVOD) addresses this limitation but…
medical image detectionContrastive LearningObject DetectionSpectMamba: Integrating Frequency and State Space Models for Enhanced Medical Image Detection
Abnormality detection in medical imaging is a critical task requiring both high efficiency and accuracy to support effective diagnosis. While convolutional neural networks (CNNs) and Transformer-based models are widely u…
medical image detectionA deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario
Background: Malaria is a critical and potentially fatal disease caused by the Plasmodium parasite and is responsible for more than 600,000 deaths globally. Early and accurate detection of malaria parasites is crucial f…
DiagnosticMalaria Falciparum DetectionMalaria Malariae DetectionMalaria Ovale Detection+5Pediatric 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+2Enhancing Wrist Fracture Detection with YOLO
Diagnosing and treating abnormalities in the wrist, specifically distal radius, and ulna fractures, is a crucial concern among children, adolescents, and young adults, with a higher incidence rate during puberty. However…
Anomaly DetectionFracture detectionmedical image detectionMedical Object Detection+3Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection
Children often suffer wrist injuries in daily life, while fracture injuring radiologists usually need to analyze and interpret X-ray images before surgical treatment by surgeons. The development of deep learning has enab…
Fracture detectionmedical image detectionMedical Object Detectionobject-detection+1Higher-order Structure Based Anomaly Detection on Attributed Networks
Anomaly detection (such as telecom fraud detection and medical image detection) has attracted the increasing attention of people. The complex interaction between multiple entities widely exists in the network, which can …
Anomaly DetectionAttributeFraud DetectionGraph Attention+2Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images -- Nevus & Melanoma
Automated region of interest detection in histopathological image analysis is a challenging and important topic with tremendous potential impact on clinical practice. The deep-learning methods used in computational patho…
medical image detectionwhole slide imagesYOLOv9 for Fracture Detection in Pediatric Wrist Trauma X-ray Images
The introduction of YOLOv9, the latest version of the You Only Look Once (YOLO) series, has led to its widespread adoption across various scenarios. This paper is the first to apply the YOLOv9 algorithm model to the frac…
Data AugmentationFracture detectionmedical image detectionMedical Object Detection+1YOLOv8-AM: YOLOv8 Based on Effective Attention Mechanisms 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 detectionmedical image detectionMedical Object DetectionObject Detection+1EAFP-Med: An Efficient Adaptive Feature Processing Module Based on Prompts for Medical Image Detection
In the face of rapid advances in medical imaging, cross-domain adaptive medical image detection is challenging due to the differences in lesion representations across various medical imaging technologies. To address this…
Medical Image Analysismedical image detectionBGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection
You Only Look Once (YOLO)-based object detectors have shown remarkable accuracy for automated brain tumor detection. In this paper, we develop a novel BGF-YOLO architecture by incorporating Bi-level routing attention, Ge…
2D Object DetectionMedical Diagnosismedical image detectionMedical Object Detection+3RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance of using YOLO networks is scarcely invest…
2D Object DetectionMedical Diagnosismedical image detectionMedical Object Detection+3CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer
Blood cell detection is a typical small-scale object detection problem in computer vision. In this paper, we propose a CST-YOLO model for blood cell detection based on YOLOv7 architecture and enhance it with the CNN-Swin…
2D Object DetectionBlood Cell DetectionCell DetectionMedical Diagnosis+6Fracture Detection in Pediatric Wrist Trauma X-ray Images Using YOLOv8 Algorithm
Hospital emergency departments frequently receive lots of bone fracture cases, with pediatric wrist trauma fracture accounting for the majority of them. Before pediatric surgeons perform surgery, they need to ask patient…
Data AugmentationFracture detectionmedical image detectionMedical Object Detection+1MONAI: An open-source framework for deep learning in healthcare
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagnose, prognose, and intervene on human di…
Deep LearningMedical Image Classificationmedical image detectionMedical Image Registration+1Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images
Automated region of interest detection in histopathological image analysis is a challenging and important topic with tremendous potential impact on clinical practice. The deep-learning methods used in computational patho…
medical image detectionwhole slide imagesOpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms
In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelligence (AI) computing platforms. Various …
image-classificationImage ClassificationMedical Image AnalysisMedical Image Classification+2PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization
The burst of applications empowered by massive data have aroused unprecedented privacy concerns in AI society. Currently, data confidentiality protection has been one core issue during deep model training. Federated Lear…
Federated Learningmedical image detectionPersonalized Federated LearningPrivacy Preserving