In this study, we trained two convolutional neural networks to automatically identify the third vertebral level and segment the abdominal muscle in contrast enhanced abdominal CT images. In the future, these models will be used to determine reference ranges for skeletal muscle mass in children by age for the purpose of identifying patient characteristics associated with differences in skeletal muscle mass. Read More

Meeting name: SPR 2020 Annual Meeting & Postgraduate Course , 2020

Authors: Castiglione James, Gilligan Leah, Somasundaram Elanchezhian, Trout Andrew, Brady Samuel

Keywords: Neural Network, Segmentation, Deep Learning

To develop an optimized AI model to automatically segment lung volumes from pulmonary magnetic resonance images (MRI) and generate tidal volume calculations for neonatal patients with chronic lung disease of prematurity (bronchopulmonary dysplasia, BPD). Read More

Meeting name: SPR 2024 Annual Meeting & Postgraduate Course , 2024

Authors: Mahalingam Neeraja, Bates Alister, Higano Nara, Gunatilaka Chamindu, Woods Jason, Somasundaram Elanchezhian

Keywords: Bronchopulmonary Dysplasia, MRI, Deep Learning

At our institution, airway radiographs are routinely checked by the radiologist to ensure diagnostic image quality prior to the technologist completing the examination. These checks interrupt the workflow for both the technologist and radiologist. In this study, we develop and validate a deep learning algorithm to detect non-diagnostic lateral airway radiographs. Read More

Meeting name: SPR 2020 Annual Meeting & Postgraduate Course , 2020

Authors: Somasundaram Elanchezhian, Brady Samuel, Crotty Eric, Trout Andrew, Anton Christopher, Towbin Alexander, Coley Brian, Dillman Jonathan

Keywords: Deep learning, Airway, Xray