PURPOSE: Medical image segmentation is an essential component of medical image analysis. Accurate segmentation can assist doctors in diagnosis and relieve their fatigue. Although several image segmentation methods based on U-Net have been proposed, t...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Jul 31, 2020
Lung cancer remains the most common cause of cancer death worldwide. Recent advances in lung cancer screening, radiotherapy, surgical techniques, and systemic therapy have led to increasing complexity in diagnosis, treatment decision-making, and asse...
Lung cancer is a major cause of death worldwide. As early detection can improve outcome, regular screening is of great interest, especially for certain risk groups. Besides low-dose computed tomography, chest X-ray is a potential option for screening...
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jul 29, 2020
To date, coronavirus disease 2019 (COVID-19) has infected millions of people worldwide. Ultrasound plays an indispensable role in the diagnosis, monitoring, and follow-up of patients with COVID-19. In this study, we used a robotic tele-echography sys...
This study employed deep-learning convolutional neural networks to stage lung disease severity of Coronavirus Disease 2019 (COVID-19) infection on portable chest x-ray (CXR) with radiologist score of disease severity as ground truth. This study consi...
Background It is uncertain whether a deep learning-based automatic detection algorithm (DLAD) for identifying malignant nodules on chest radiographs will help diagnose lung cancers. Purpose To evaluate the efficacy of using a DLAD in observer perform...
OBJECTIVE: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression of COVID-19 using thick-section chest CT images.
BACKGROUND: When pulmonary complications occur, postlobectomy patients have a higher mortality rate, increased length of stay, and higher readmission rates. Because of a lack of high-quality consolidated clinical data, it is challenging to assess and...
OBJECTIVES: To evaluate the calibration of a deep learning (DL) model in a diagnostic cohort and to improve model's calibration through recalibration procedures.