237 citations · 300 across the 10 of their papers we have counts for
7 papers · 1 filter
Cross Modality Medical Image Synthesis for Improving Liver Segmentation
Muhammad Rafiq, Hazrat Ali, Ghulam Mujtaba +2
Deep learning-based computer-aided diagnosis (CAD) of medical images requires large datasets. However, the lack of large publicly available labeled datasets limits the development…
An Early Investigation into the Utility of Multimodal Large Language Models in Medical Imaging
Sulaiman Khan, Md. Rafiul Biswas, Alina Murad +2
Recent developments in multimodal large language models (MLLMs) have spurred significant interest in their potential applications across various medical imaging domains. On the one…
Improving diagnosis and prognosis of lung cancer using vision transformers: A scoping review
Hazrat Ali, Farida Mohsen, Zubair Shah
Vision transformer-based methods are advancing the field of medical artificial intelligence and cancer imaging, including lung cancer applications. Recently, many researchers have…
Leveraging GANs for data scarcity of COVID-19: Beyond the hype
Hazrat Ali, Christer Gronlund, Zubair Shah
Artificial Intelligence (AI)-based models can help in diagnosing COVID-19 from lung CT scans and X-ray images; however, these models require large amounts of data for training and…
Brain Tumor Synthetic Data Generation with Adaptive StyleGANs
Usama Tariq, Rizwan Qureshi, Anas Zafar +5
Generative models have been very successful over the years and have received significant attention for synthetic data generation. As deep learning models are getting more and more…
Spot the fake lungs: Generating Synthetic Medical Images using Neural Diffusion Models
Hazrat Ali, Shafaq Murad, Zubair Shah
Generative models are becoming popular for the synthesis of medical images. Recently, neural diffusion models have demonstrated the potential to generate photo-realistic images of…
Combating COVID-19 using Generative Adversarial Networks and Artificial Intelligence for Medical Images: A Scoping Review
Hazrat Ali, Zubair Shah
This review presents a comprehensive study on the role of GANs in addressing the challenges related to COVID-19 data scarcity and diagnosis. It is the first review that summarizes…