Synthetic Skull CT Generation with Generative Adversarial Networks to Train Deep Learning Models for Clinical Transcranial Ultrasound

1 code implementation • 1 Aug 2023 • Kasra Naftchi-Ardebili, Karanpartap Singh, Reza Pourabolghasem, Pejman Ghanouni, Gerald R. Popelka, Kim Butts Pauly

To overcome these challenges, we propose a generative adversarial network (SkullGAN) to create large datasets of synthetic skull CT slices, geared towards training models for transcranial ultrasound.

Generative Adversarial Network

Knowledge Discovery In Nanophotonics Using Geometric Deep Learning

no code implementations • 16 Sep 2019 • Yashar Kiarashinejad, Mohammadreza Zandehshahvar, Sajjad Abdollahramezani, Omid Hemmatyar, Reza Pourabolghasem, Ali Adibi

More importantly, the one-class SVM algorithm can be trained to provide the degree of feasibility (or unfeasibility) of a response from a given nanostructure.

Dimensionality Reduction

Winning Isn't Everything: Enhancing Game Development with Intelligent Agents

no code implementations • 25 Mar 2019 • Yunqi Zhao, Igor Borovikov, Fernando De Mesentier Silva, Ahmad Beirami, Jason Rupert, Caedmon Somers, Jesse Harder, John Kolen, Jervis Pinto, Reza Pourabolghasem, James Pestrak, Harold Chaput, Mohsen Sardari, Long Lin, Sundeep Narravula, Navid Aghdaie, Kazi Zaman

We discuss two fundamental metrics based on which we measure the human-likeness of agents, namely skill and style, which are multi-faceted concepts with practical implications outlined in this paper.