182 citations · 243 across the 15 of their papers we have counts for
16 papers
Learning complete and explainable visual representations from itemized text supervision
Yiwei Lyu, Chenhui Zhao, Soumyanil Banerjee +5
Training vision models with language supervision enables general and transferable representations. However, many visual domains, especially non-object-centric domains such as medic…
Health system learning achieves generalist neuroimaging models
Akhil Kondepudi, Akshay Rao, Chenhui Zhao +14
Frontier artificial intelligence (AI) models, such as OpenAI's GPT-5 and Meta's DINOv3, have advanced rapidly through training on internet-scale public data, yet such systems lack…
CodeV: Code with Images for Faithful Visual Reasoning via Tool-Aware Policy Optimization
Xinhai Hou, Shaoyuan Xu, Manan Biyani +4
Agentic vision-language models are increasingly trained to "think with images" by calling image operations. However, we show that high final-answer accuracy often hides unfaithful…
Learning neuroimaging models from health system-scale data
Yiwei Lyu, Samir Harake, Asadur Chowdury +18
Neuroimaging is a ubiquitous tool for evaluating patients with neurological diseases. The global demand for magnetic resonance imaging (MRI) studies has risen steadily, placing sig…
Intelligent Histology for Tumor Neurosurgery
Xinhai Hou, Akhil Kondepudi, Cheng Jiang +27
The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standard-of-care intraoperative pathol…
Towards Scalable Language-Image Pre-training for 3D Medical Imaging
Chenhui Zhao, Yiwei Lyu, Asadur Chowdury +6
The scalability of current language-image pre-training for 3D medical imaging, such as CT and MRI, is constrained by the need for radiologists to manually curate raw clinical studi…
CNS-Obsidian: A Neurosurgical Vision-Language Model Built From Scientific Publications
Anton Alyakin, Jaden Stryker, Daniel Alexander Alber +29
General-purpose VLMs demonstrate impressive capabilities, but their opaque training on uncurated internet data poses critical limitations for high-stakes decision-making, such as i…
Super-resolution of biomedical volumes with 2D supervision
Cheng Jiang, Alexander Gedeon, Yiwei Lyu +7
Volumetric biomedical microscopy has the potential to increase the diagnostic information extracted from clinical tissue specimens and improve the diagnostic accuracy of both human…
Step-Calibrated Diffusion for Biomedical Optical Image Restoration
Yiwei Lyu, Sung Jik Cha, Cheng Jiang +7
High-quality, high-resolution medical imaging is essential for clinical care. Raman-based biomedical optical imaging uses non-ionizing infrared radiation to evaluate human tissues…
Development and validation of an artificial intelligence model to accurately predict spinopelvic parameters
Edward S. Harake, Joseph R. Linzey, Cheng Jiang +9
Objective. Achieving appropriate spinopelvic alignment has been shown to be associated with improved clinical symptoms. However, measurement of spinopelvic radiographic parameters…
A self-supervised framework for learning whole slide representations
Xinhai Hou, Cheng Jiang, Akhil Kondepudi +4
Whole slide imaging is fundamental to biomedical microscopy and computational pathology. Previously, learning representations for gigapixel-sized whole slide images (WSIs) has reli…
Fine-grained Text Style Transfer with Diffusion-Based Language Models
Yiwei Lyu, Tiange Luo, Jiacheng Shi +2
Diffusion probabilistic models have shown great success in generating high-quality images controllably, and researchers have tried to utilize this controllability into text generat…
Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging
Todd C. Hollon, Cheng Jiang, Asadur Chowdury +22
Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic t…
Hierarchical discriminative learning improves visual representations of biomedical microscopy
Cheng Jiang, Xinhai Hou, Akhil Kondepudi +5
Learning high-quality, self-supervised, visual representations is essential to advance the role of computer vision in biomedical microscopy and clinical medicine. Previous work has…
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology
Cheng Jiang, Asadur Chowdury, Xinhai Hou +7
Accurate intraoperative diagnosis is essential for providing safe and effective care during brain tumor surgery. Our standard-of-care diagnostic methods are time, resource, and lab…
Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence
Cheng Jiang, Abhishek Bhattacharya, Joseph Linzey +19
Background: Accurate diagnosis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative diagnosis can be challenging due to tumor…