1 citations · 2 across the 3 of their papers we have counts for
3 papers
Generating Compositional Scenes via Text-to-image RGBA Instance Generation
Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang +2
Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditio…
Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT
Alessandro Fontanella, Wenwen Li, Grant Mair +6
Computed Tomography (CT) is commonly used to image acute ischemic stroke (AIS) patients, but its interpretation by radiologists is time-consuming and subject to inter-observer vari…
Challenges of building medical image datasets for development of deep learning software in stroke
Alessandro Fontanella, Wenwen Li, Grant Mair +7
Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited. Furthermore, the dat…