14 citations · 26 across the 3 of their papers we have counts for
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cs.CV2026
Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context
Suneeta Mall, Vladimir Nekrasov, Ashnil Kumar +5
Imaging demand is growing faster than the radiology workforce can expand, and reporting backlogs cannot be resolved through training and recruitment alone. The most direct opportun…
cs.CV2018
Generative Visual Rationales
Jarrel Seah, Jennifer Tang, Andy Kitchen +1
Interpretability and small labelled datasets are key issues in the practical application of deep learning, particularly in areas such as medicine. In this paper, we present a semi-…
cs.CV2017★ 12 cited
Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis
Andy Kitchen, Jarrel Seah
Generative Adversarial Neural Networks (GANs) are applied to the synthetic generation of prostate lesion MRI images. GANs have been applied to a variety of natural images, is shown…