10 citations · 24 across the 7 of their papers we have counts for
8 papers
Beyond the Monitor: Mixed Reality Visualization and Multimodal AI for Enhanced Digital Pathology Workflow
Jai Prakash Veerla, Partha Sai Guttikonda, Helen H. Shang +3
Pathologists diagnose cancer using gigapixel whole-slide images (WSIs), but the current digital workflow is fragmented. These multiscale datasets often exceed 100,000 x 100,000 pix…
Analyzing Lack of Concordance Between the Proteome and Transcriptome in Paired scRNA-Seq and Multiplexed Spatial Proteomics
Jai Prakash Veerla, Jillur Rahman Saurav, Michael Robben +1
In this study, we analyze discordance between the transcriptome and proteome using paired scRNA-Seq and multiplexed spatial proteomics data from HuBMAP. Our findings highlight pers…
The State of Applying Artificial Intelligence to Tissue Imaging for Cancer Research and Early Detection
Michael Robben, Amir Hajighasemi, Mohammad Sadegh Nasr +9
Artificial intelligence represents a new frontier in human medicine that could save more lives and reduce the costs, thereby increasing accessibility. As a consequence, the rate of…
Multimodal Pathology Image Search Between H&E Slides and Multiplexed Immunofluorescent Images
Amir Hajighasemi, MD Jillur Rahman Saurav, Mohammad S Nasr +6
We present an approach for multimodal pathology image search, using dynamic time warping (DTW) on Variational Autoencoder (VAE) latent space that is fed into a ranked choice voting…
Histopathology Slide Indexing and Search: Are We There Yet?
Helen H. Shang, Mohammad Sadegh Nasr, Jai Prakash Veerla +7
The search and retrieval of digital histopathology slides is an important task that has yet to be solved. In this case study, we investigate the clinical readiness of three state-o…
Generalizability of PRS313 for breast cancer risk amongst non-Europeans in a Los Angeles biobank
Helen Shang, Yi Ding, Vidhya Venkateswaran +5
Polygenic risk scores (PRS) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors…
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image Compression
Mohammad Sadegh Nasr, Amir Hajighasemi, Paul Koomey +6
In this paper, we introduce a Variational Autoencoder (VAE) based training approach that can compress and decompress cancer pathology slides at a compression ratio of 1:512, which…
A SSIM Guided cGAN Architecture For Clinically Driven Generative Image Synthesis of Multiplexed Spatial Proteomics Channels
Jillur Rahman Saurav, Mohammad Sadegh Nasr, Paul Koomey +7
Here we present a structural similarity index measure (SSIM) guided conditional Generative Adversarial Network (cGAN) that generatively performs image-to-image (i2i) synthesis to g…