Search Results for author: Babak Saboury

Found 8 papers, 0 papers with code

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics

no code implementations20 Oct 2021 Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar, Su Ruan, Babak Saboury, Arman Rahmim

Artificial intelligence (AI) techniques have significant potential to enable effective, robust and automated image phenotyping including identification of subtle patterns.

Translation

CCS-GAN: COVID-19 CT-scan classification with very few positive training images

no code implementations1 Oct 2021 Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita, Michael Morris, Babak Saboury, Yaacov Yesha, Yelena Yesha, Phuong Nguyen, Aryya Gangopadhyay, David Chapman

CCS-GAN achieves high accuracy with few positive images and thereby greatly reduces the barrier of acquiring large training volumes in order to train a diagnostic classifier for COVID-19.

Generative Adversarial Network Style Transfer +1

A brief history of AI: how to prevent another winter (a critical review)

no code implementations3 Sep 2021 Amirhosein Toosi, Andrea Bottino, Babak Saboury, Eliot Siegel, Arman Rahmim

The field of artificial intelligence (AI), regarded as one of the most enigmatic areas of science, has witnessed exponential growth in the past decade including a remarkably wide array of applications, having already impacted our everyday lives.

speech-recognition Speech Recognition

Artificial Intelligence in PET: an Industry Perspective

no code implementations14 Jul 2021 Arkadiusz Sitek, Sangtae Ahn, Evren Asma, Adam Chandler, Alvin Ihsani, Sven Prevrhal, Arman Rahmim, Babak Saboury, Kris Thielemans

Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications.

Image Reconstruction Scheduling

Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Network

no code implementations2 Apr 2021 Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay, Yaacov Yesha, Joshua Galita, Sumeet Menon, Yelena Yesha, Babak Saboury, Michael Morris, Phuong Nguyen

We present a novel conditional Generative Adversarial Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated approximations and with the potential to generate full synthetic 3D scan volumes.

Denoising Generative Adversarial Network +1

Deep Expectation-Maximization for Semi-Supervised Lung Cancer Screening

no code implementations2 Oct 2020 Sumeet Menon, David Chapman, Phuong Nguyen, Yelena Yesha, Michael Morris, Babak Saboury

We present a semi-supervised algorithm for lung cancer screening in which a 3D Convolutional Neural Network (CNN) is trained using the Expectation-Maximization (EM) meta-algorithm.

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