30 documents found, page 1 of 3
Wia-Spine: a CBIR environment with embedded radiomic features to assess fragili...
Azevedo-Marques, Paulo Mazzoncini de
CT-based radiomics for prediction of histologic subtype and metastatic disease ...
Azevedo-Marques, Paulo Mazzoncini de
A study of MRI-based radiomics biomarkers for sacroiliitis and spondyloarthritis
Azevedo-Marques, Paulo Mazzoncini de
Machine learning techniques for computer-aided classification of active inflamm...
Azevedo-Marques, Paulo Mazzoncini de
Machine learning models to predict axial and peripheral spondyloarthritis: a co...
Azevedo-Marques, Paulo Mazzoncini de
Radiomic biomarkers for sacroiliitis diagnosis and prediction of spondyloarthri...
Azevedo-Marques, Paulo Mazzoncini de
AI-based radiomic approach in high-resolution CT images for differential diagno...
Azevedo-Marques, Paulo Mazzoncini de
Towards convolutional neural network on primary lung tumors to predict histopha...
Azevedo-Marques, Paulo Mazzoncini de
Association of bone mineral density with bone texture attributes extracted usin...
Maciel, Jamilly Gomes; Araújo, Iana Mizumukai de; Trazzi, Lucio C.; Azevedo-Marques, Paulo Mazzoncini de; Salmon, Carlos Ernesto GarridoOBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) often fails to predict fragility fractures. Quantitative textural analysis using magnetic resonance imaging (MRI) may potentially yield useful radiomic features to predict fractures. We aimed to investigate the correlation between BMD and texture attributes (TAs) extracted from MRI scans and the interobserver reproducibility of...
Inteligência artificial, aprendizado de máquina, diagnóstico auxiliado por comp...
Azevedo-Marques, Paulo Mazzoncini de