182 citations · 236 across the 5 of their papers we have counts for
6 papers
Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging
Haoxu Huang, Long Chen, Jingyun Chen +8
Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic and fluid-sensitive T2-weighted (T…
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…
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…