Automated detection of pulmonary embolism from CT-angiograms using deep learning
H Huhtanen, M Nyman, T Mohsen, A Virkki… - BMC Medical …, 2022 - Springer
Background The aim of this study was to develop and evaluate a deep neural network
model in the automated detection of pulmonary embolism (PE) from computed tomography …
model in the automated detection of pulmonary embolism (PE) from computed tomography …
Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism
Pulmonary Embolism (PE) represents a thrombus (“blood clot”), usually originating from a
lower extremity vein, that travels to the blood vessels in the lung, causing vascular …
lower extremity vein, that travels to the blood vessels in the lung, causing vascular …
Automatic inter-frame patient motion correction for dynamic cardiac PET using deep learning
Patient motion during dynamic PET imaging can induce errors in myocardial blood flow
(MBF) estimation. Motion correction for dynamic cardiac PET is challenging because the …
(MBF) estimation. Motion correction for dynamic cardiac PET is challenging because the …
Multimodal fusion models for pulmonary embolism mortality prediction
Pulmonary embolism (PE) is a common, life threatening cardiovascular emergency. Risk
stratification is one of the core principles of acute PE management and determines the …
stratification is one of the core principles of acute PE management and determines the …
SCUNet++: Swin-UNet and CNN Bottleneck Hybrid Architecture with Multi-Fusion Dense Skip Connection for Pulmonary Embolism CT Image Segmentation
Pulmonary embolism (PE) is a prevalent lung disease that can lead to right ventricular
hypertrophy and failure in severe cases, ranking second in severity only to myocardial …
hypertrophy and failure in severe cases, ranking second in severity only to myocardial …
Attention based CNN-LSTM network for pulmonary embolism prediction on chest computed tomography pulmonary angiograms
With more than 60,000 deaths annually in the United States, Pulmonary Embolism (PE) is
among the most fatal cardiovascular diseases. It is caused by an artery blockage in the lung; …
among the most fatal cardiovascular diseases. It is caused by an artery blockage in the lung; …
Deep learning for automatic pulmonary embolism identification using CTA images
H Khachnaoui, M Agrébi, S Halouani… - 2022 6th International …, 2022 - ieeexplore.ieee.org
Background; The diagnosis of diseases with Deep Learning (DL) methods such as
Convolution Neural Network (CNN) receives spectacular attention due to their efficacy in the …
Convolution Neural Network (CNN) receives spectacular attention due to their efficacy in the …
Detecting pulmonary embolism using deep neural networks
J Akilandeswaria, G Jothib… - International Journal …, 2021 - ijpe-online.com
Medical image processing is a method to create visual representations of the internal parts
of the human body such as organs or tissues which helps diagnose and monitor diseases …
of the human body such as organs or tissues which helps diagnose and monitor diseases …
Missed incidental pulmonary embolism: harnessing artificial intelligence to assess prevalence and improve quality improvement opportunities
B Wildman-Tobriner, L Ngo, JG Mammarappallil… - Journal of the American …, 2021 - Elsevier
Purpose Incidental pulmonary embolism (IPE) can be found on body CT. The aim of this
study was to evaluate the feasibility of using artificial intelligence to identify missed IPE on a …
study was to evaluate the feasibility of using artificial intelligence to identify missed IPE on a …
Weakly supervised attention model for RV strain classification from volumetric CTPA scans
Background and objective: Evaluation of the right ventricle (RV) is a key component of the
clinical assessment of many cardiovascular and pulmonary disorders. In this work, we focus …
clinical assessment of many cardiovascular and pulmonary disorders. In this work, we focus …