12 citations · 37 across the 42 of their papers we have counts for
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Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics
Yukun Zhou, Paul Nderitu, Jocelyn Hui Lin Goh +20
Medical foundation models, pre-trained with large-scale clinical data, demonstrate strong performance in diverse clinically relevant applications. RETFound, trained on nearly one m…
A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs
Niccolò McConnell, Pardeep Vasudev, Daisuke Yamada +13
Low-dose computed tomography (LDCT) imaging employed in lung cancer screening (LCS) programs is increasing in uptake worldwide. LCS programs herald a generational opportunity to si…
Is an Ultra Large Natural Image-Based Foundation Model Superior to a Retina-Specific Model for Detecting Ocular and Systemic Diseases?
Qingshan Hou, Yukun Zhou, Jocelyn Hui Lin Goh +19
The advent of foundation models (FMs) is transforming medical domain. In ophthalmology, RETFound, a retina-specific FM pre-trained sequentially on 1.4 million natural images and 1.…
MRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels
Moucheng Xu, Yukun Zhou, Tobias Goodwin-Allcock +4
We introduce and demonstrate a new paradigm for quantitative parameter mapping in MRI. Parameter mapping techniques, such as diffusion MRI and quantitative MRI, have the potential…
MONICA: Benchmarking on Long-tailed Medical Image Classification
Lie Ju, Siyuan Yan, Yukun Zhou +4
Long-tailed learning is considered to be an extremely challenging problem in data imbalance learning. It aims to train well-generalized models from a large number of images that fo…
Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model
Meng Wang, Tian Lin, Aidi Lin +46
Previous foundation models for fundus images were pre-trained with limited disease categories and knowledge base. Here we introduce a knowledge-rich vision-language model (RetiZero…
Deep learning to estimate the physical proportion of infected region of lung for COVID-19 pneumonia with CT image set
Wei Wu, Yu Shi, Xukun Li +5
Utilizing computed tomography (CT) images to quickly estimate the severity of cases with COVID-19 is one of the most straightforward and efficacious methods. Two tasks were studied…