2 code implementations • 7 Sep 2023 • Ahmed H. Shahin, An Zhao, Alexander C. Whitehead, Daniel C. Alexander, Joseph Jacob, David Barber
We demonstrate that our approach forms a consistent estimator for the event model parameters, even in the absence of uncensored data.
no code implementations • 20 Mar 2023 • Ahmed H. Shahin, Yan Zhuang, Noha El-Zehiry
Furthermore, our framework accommodates multiple edits to the segmentation output in a sequential manner without compromising previous edits.
2 code implementations • 21 Mar 2022 • Ahmed H. Shahin, Joseph Jacob, Daniel C. Alexander, David Barber
To this end, we propose a probabilistic model that captures the dependencies between the observed clinical variables and imputes missing ones.
no code implementations • 4 Apr 2020 • Ahmed H. Shahin, Prateek Munjal, Ling Shao, Shadab Khan
We propose a novel approach for effectively encoding the user input from extreme points and corrective clicks, in a novel and scalable manner that allows the network to work with a variable number of clicks, including corrective clicks for output refinement.
1 code implementation • 6 Jun 2019 • Shadab Khan, Ahmed H. Shahin, Javier Villafruela, Jianbing Shen, Ling Shao
To automate the process of segmenting an anatomy of interest, we can learn a model from previously annotated data.
no code implementations • 26 Jan 2019 • Ahmed H. Shahin, Karim Amer, Mustafa A. Elattar
The prevalence of skin melanoma is rapidly increasing as well as the recorded death cases of its patients.