11 citations · 12 across the 3 of their papers we have counts for
3 papers
Boosting Radiology Report Generation by Infusing Comparison Prior
Sanghwan Kim, Farhad Nooralahzadeh, Morteza Rohanian +5
Recent transformer-based models have made significant strides in generating radiology reports from chest X-ray images. However, a prominent challenge remains: these models often la…
Progressive Transformer-Based Generation of Radiology Reports
Farhad Nooralahzadeh, Nicolas Perez Gonzalez, Thomas Frauenfelder +2
Inspired by Curriculum Learning, we propose a consecutive (i.e., image-to-text-to-text) generation framework where we divide the problem of radiology report generation into two ste…
Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning
Mizuho Nishio, Koji Fujimoto, Kaori Togashi
Rationale and objectives: Several studies have evaluated the usefulness of deep learning for lung segmentation using chest x-ray (CXR) images with small- or medium-sized abnormal f…