BACKGROUND: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 1, 2021
This paper focuses on the thorax disease classification problem in chest X-ray (CXR) images. Different from the generic image classification task, a robust and stable CXR image analysis system should consider the unique characteristics of CXR images....
BACKGROUND: We sought to evaluate the association of metabolic syndrome (MetS) and computed tomography (CT)-derived cardiometabolic biomarkers (non-alcoholic fatty liver disease [NAFLD] and epicardial adipose tissue [EAT] measures) with long-term ris...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Chest radiographs are the most common diagnostic exam in emergency rooms and intensive care units today. Recently, a number of researchers have begun working on large chest X-ray datasets to develop deep learning models for recognition of a handful o...
PURPOSE: To evaluate the usefulness of the deep learning image reconstruction (DLIR) to enhance the image quality of abdominal CT, compared to iterative reconstruction technique.
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. Th...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jan 13, 2021
PURPOSE: This study aimed to assess the noise characteristics of ultra-high-resolution computed tomography (UHRCT) with deep learning-based reconstruction (DLR).
This paper explores how well deep learning models trained on chest CT images can diagnose COVID-19 infected people in a fast and automated process. To this end, we adopted advanced deep network architectures and proposed a transfer learning strategy ...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jan 11, 2021
PURPOSE: To assess whether a deep learning image reconstruction algorithm (TrueFidelity) can preserve the image texture of conventional filtered back projection (FBP) at reduced dose levels attained by ASIR-V in chest CT.