55 citations · 58 across the 2 of their papers we have counts for
2 papers
cs.CV2021★ 3 cited
Comparing radiologists' gaze and saliency maps generated by interpretability methods for chest x-rays
Ricardo Bigolin Lanfredi, Ambuj Arora, Trafton Drew +2
The interpretability of medical image analysis models is considered a key research field. We use a dataset of eye-tracking data from five radiologists to compare the outputs of int…
eess.IV2021★ 55 cited
REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays
Ricardo Bigolin Lanfredi, Mingyuan Zhang, William F. Auffermann +6
Deep learning has shown recent success in classifying anomalies in chest x-rays, but datasets are still small compared to natural image datasets. Supervision of abnormality localiz…