PURPOSE: To investigate the feasibility of an artificial intelligence (AI)-based semi-automated segmentation for the extraction of ultrasound (US)-derived radiomics features in the characterization of focal breast lesions (FBLs).
Biomedical physics & engineering express
May 7, 2024
. Radiomics is a promising valuable analysis tool consisting in extracting quantitative information from medical images. However, the extracted radiomics features are too sensitive to variations in used image acquisition and reconstruction parameters...
Carotid atherosclerosis plays a substantial role in cardiovascular morbidity and mortality. Given the multifaceted impact of this disease, there has been increasing interest in harnessing artificial intelligence (AI) and radiomics as complementary to...
RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CT) to identify the primary source of liver metastases.
AIM: This study aimed to develop highly precise radiomics and deep learning models to accurately detect acute lymphoblastic leukemia (ALL) using a T1WI image.
RATIONALE AND OBJECTIVES: This study aims to evaluate the capability of machine learning algorithms in utilizing radiomic features extracted from cine-cardiac magnetic resonance (CMR) sequences for differentiating between ischemic cardiomyopathy (ICM...
RATIONALE AND OBJECTIVES: To develop and validate a predictive model for osteoporosis and osteopenia prediction by fusing deep transfer learning (DTL) features and classical radiomics features based on single-source dual-energy computed tomography (C...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
May 1, 2024
We aimed to investigate the effects of F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) and machine learning-generated radiomic biomarkers. We extracted 1,037 F-FDG PET radiomic features q...
International journal of surgery (London, England)
May 1, 2024
BACKGROUND: Occult peritoneal metastases (OPM) in patients with pancreatic ductal adenocarcinoma (PDAC) are frequently overlooked during imaging. The authors aimed to develop and validate a computed tomography (CT)-based deep learning-based radiomics...
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