activity
20202022
most citedA brief history of AI: how to prevent another winter (a critical review)

187 citations · 207 across the 11 of their papers we have counts for

collaborators

11 papers

physics.med-ph2022★ 2 cited

Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine -- The Bethesda Report (AI Summit 2022)

Arman Rahmim, Tyler J. Bradshaw, Irène Buvat +10

The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought together various community me…

physics.med-ph2021★ 1 cited

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

Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar +3

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

eess.IV2021

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

Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita +7

We present a novel algorithm that is able to classify COVID-19 pneumonia from CT Scan slices using a very small sample of training images exhibiting COVID-19 pneumonia in tandem wi…

cs.AI2021★ 187 cited

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

Amirhosein Toosi, Andrea Bottino, Babak Saboury +2

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 a…

physics.med-ph2021★ 1 cited

Role of AI in Theranostics: Towards Routine Personalized Radiopharmaceutical Therapies

Julia Brosch-Lenz, Fereshteh Yousefirizi, Katherine Zukotynski +5

We highlight emerging uses of artificial intelligence (AI) in the field of theranostics, focusing on its significant potential to enable routine and reliable personalization of rad…

physics.med-ph2021★ 7 cited

Objective task-based evaluation of artificial intelligence-based medical imaging methods: Framework, strategies and role of the physician

Abhinav K. Jha, Kyle J. Myers, Nancy A. Obuchowski +5

Artificial intelligence (AI)-based methods are showing promise in multiple medical-imaging applications. Thus, there is substantial interest in clinical translation of these method…

cs.CV2021

Artificial Intelligence in PET: an Industry Perspective

Arkadiusz Sitek, Sangtae Ahn, Evren Asma +6

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

physics.med-ph2021

Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging

Fereshteh Yousefirizi, Abhinav K. Jha, Julia Brosch-Lenz +2

Artificial intelligence (AI) techniques for image-based segmentation have garnered much attention in recent years. Convolutional neural networks (CNNs) have shown impressive result…

eess.IV2021

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

Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay +7

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 a…

cs.LG2020★ 9 cited

Deep Expectation-Maximization for Semi-Supervised Lung Cancer Screening

Sumeet Menon, David Chapman, Phuong Nguyen +3

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.…

cs.LG2020

Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN

Sumeet Menon, Joshua Galita, David Chapman +7

COVID-19 is a novel infectious disease responsible for over 800K deaths worldwide as of August 2020. The need for rapid testing is a high priority and alternative testing strategie…