Pulmonary Embolism Detection
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Benchmarks
PE-CAD FPRED
Most implemented
Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Papers
Using Unsupervised Domain Adaptation Semantic Segmentation for Pulmonary Embolism Detection in Computed Tomography Pulmonary Angiogram (CTPA) Images
While deep learning has demonstrated considerable promise in computer-aided diagnosis for pulmonary embolism (PE), practical deployment in Computed Tomography Pulmonary Angiography (CTPA) is often hindered by "domain shi…
Unsupervised Domain AdaptationPulmonary Embolism DetectionSemantic SegmentationContrastive LearningDAUNet: A Lightweight UNet Variant with Deformable Convolutions and Parameter-Free Attention for Medical Image Segmentation
Medical image segmentation plays a pivotal role in automated diagnostic and treatment planning systems. In this work, we present DAUNet, a novel lightweight UNet variant that integrates Deformable V2 Convolutions and Par…
Pulmonary Embolism DetectionMedical Image SegmentationDeep learning in computed tomography pulmonary angiography imaging: a dual-pronged approach for pulmonary embolism detection
The increasing reliance on Computed Tomography Pulmonary Angiography (CTPA) for Pulmonary Embolism (PE) diagnosis presents challenges and a pressing need for improved diagnostic solutions. The primary objective of this s…
Diagnosticobject-detectionObject DetectionPulmonary Embolism Detection+2PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism Diagnosis
Previous deep learning efforts have focused on improving the performance of Pulmonary Embolism(PE) diagnosis from Computed Tomography (CT) scans using Convolutional Neural Networks (CNN). However, the features from CT sc…
Computed Tomography (CT)Contrastive LearningPulmonary Embolism DetectionAnatomically aware dual-hop learning for pulmonary embolism detection in CT pulmonary angiograms
Pulmonary Embolisms (PE) represent a leading cause of cardiovascular death. While medical imaging, through computed tomographic pulmonary angiography (CTPA), represents the gold standard for PE diagnosis, it is still sus…
Deep LearningPulmonary Embolism DetectionDetecting Pulmonary Embolism from Computed Tomography Using Convolutional Neural Network
The clinical symptoms of pulmonary embolism (PE) are very diverse and non-specific, which makes it difficult to diagnose. In addition, pulmonary embolism has multiple triggers and is one of the major causes of vascular d…
Pulmonary Embolism Detection