PT Journal
AU Sonia Baeza
   Debora Gil
   Ignasi Garcia Olive
   Maite Salcedo Pujantell
   Jordi Deportos
   Carles Sanchez
   Guillermo Torres
   Gloria Moragas
   Antoni Rosell
TI Correction: A novel intelligent radiomic analysis of perfusion SPECT/CT images to optimize pulmonary embolism diagnosis in COVID-19 patients
SO European Journal of Nuclear Medicine and Molecular Imaging
JI EJNMMI PHYSICS
PY 2023
BP 13
VL 10
IS 1
DI 10.1186/s40658-023-00532-z
DE early diagnosis; Lung Cancer; nodule diagnosis; Radiomics; Screening
AB This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level.
ER