1 code implementation • 15 Sep 2020 • Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, Joy Wu, Arjun Sharma, Matthew Tong, Shafiq Abedin, David Beymer, Vandana Mukherjee, Elizabeth A. Krupinski, Mehdi Moradi
We report deep learning experiments that utilize the attention maps produced by eye gaze dataset to show the potential utility of this data.
no code implementations • MIDL 2019 • Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan
In addition to the classification loss, an attention loss was added during training to help the network focus attention on PE.
no code implementations • 5 Oct 2019 • Deepta Rajan, David Beymer, Shafiqul Abedin, Ehsan Dehghan
Pulmonary embolisms (PE) are known to be one of the leading causes for cardiac-related mortality.
no code implementations • 5 Jan 2019 • Deepta Rajan, David Beymer, Girish Narayan
Though deep neural networks have achieved unprecedented success in predictive modeling, they rely solely on discriminative models that can generalize poorly to unseen classes.
no code implementations • 3 Dec 2018 • Nathaniel Braman, David Beymer, Ehsan Dehghan
We explore a solution for learning disease signatures from weakly, yet easily obtainable, annotated volumetric medical imaging data by analyzing 3D volumes as a sequence of 2D images.