Artificial intelligence-driven assessment of radiological images for COVID-19
Y Bouchareb, PM Khaniabadi, F Al Kindi… - Computers in biology …, 2021 - Elsevier
Artificial Intelligence (AI) methods have significant potential for diagnosis and prognosis of
COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients …
COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients …
COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients
Background We aimed to analyze the prognostic power of CT-based radiomics models
using data of 14,339 COVID-19 patients. Methods Whole lung segmentations were …
using data of 14,339 COVID-19 patients. Methods Whole lung segmentations were …
High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms
We aimed to construct a prediction model based on computed tomography (CT) radiomics
features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A …
features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A …
Automatic fetal biometry prediction using a novel deep convolutional network architecture
MG Oghli, A Shabanzadeh, S Moradi, N Sirjani… - Physica Medica, 2021 - Elsevier
Purpose Fetal biometric measurements face a number of challenges, including the presence
of speckle, limited soft-tissue contrast and difficulties in the presence of low amniotic fluid …
of speckle, limited soft-tissue contrast and difficulties in the presence of low amniotic fluid …
Mortality prediction of COVID-19 patients using radiomic and neural network features extracted from a wide chest X-ray sample size: A robust approach for different …
M Iori, C Di Castelnuovo, L Verzellesi, G Meglioli… - Applied Sciences, 2022 - mdpi.com
Aim: The aim of this study was to develop robust prognostic models for mortality prediction of
COVID-19 patients, applicable to different sets of real scenarios, using radiomic and neural …
COVID-19 patients, applicable to different sets of real scenarios, using radiomic and neural …
A novel unsupervised covid lung lesion segmentation based on the lung tissue identification
FG Khah, S Mostafapour, S Shojaerazavi… - arXiv preprint arXiv …, 2022 - arxiv.org
This study aimed to evaluate the performance of a novel unsupervised deep learning-based
framework for automated infections lesion segmentation from CT images of Covid patients …
framework for automated infections lesion segmentation from CT images of Covid patients …
Machine and deep learning algorithms for COVID-19 mortality prediction using clinical and radiomic features
L Verzellesi, A Botti, M Bertolini, V Trojani, G Carlini… - Electronics, 2023 - mdpi.com
Aim: Machine learning (ML) and deep learning (DL) predictive models have been employed
widely in clinical settings. Their potential support and aid to the clinician of providing an …
widely in clinical settings. Their potential support and aid to the clinician of providing an …
A Novel Unsupervised COVID-19 Lesion Segmentation from CT Images Based-on the Lung Tissue Detection
F Gholamiankhah, S Mostafapour… - 2021 IEEE Nuclear …, 2021 - ieeexplore.ieee.org
Image segmentation plays a significant role in quantitative image analysis. Lung
segmentation of CT images has received more importance in fighting against COVID-19. In …
segmentation of CT images has received more importance in fighting against COVID-19. In …
A Novel Unsupervised Approach for COVID-19 Lung Lesion Detection Based on Object Completion Technique
S Mostafapour, F Gholamiankhah… - 2021 IEEE Nuclear …, 2021 - ieeexplore.ieee.org
Automated segmentation of COVID-19 lesions from CT images is a prerequisite for
quantitative assessment of the infections, enabling accurate and timely screening of the …
quantitative assessment of the infections, enabling accurate and timely screening of the …
Deep Learning-based Automated Delineation of Head and Neck Malignant Lesions from PET Images
Accurate delineation of the gross tumor volume (GTV) is critical for treatment planning in
radiation oncology. This task is very challenging owing to the irregular and diverse shapes …
radiation oncology. This task is very challenging owing to the irregular and diverse shapes …