10 citations · 25 across the 12 of their papers we have counts for
12 papers
UNIStainNet: Foundation-Model-Guided Virtual Staining of H&E to IHC
Jillur Rahman Saurav, Thuong Le Hoai Pham, Pritam Mukherjee +3
Virtual immunohistochemistry (IHC) staining from hematoxylin and eosin (H&E) images can accelerate diagnostics by providing preliminary molecular insight directly from routine sect…
Cross-Domain Image Synthesis: Generating H&E from Multiplex Biomarker Imaging
Jillur Rahman Saurav, Mohammad Sadegh Nasr, Jacob M. Luber
While multiplex immunofluorescence (mIF) imaging provides deep, spatially-resolved molecular data, integrating this information with the morphological standard of Hematoxylin & Eos…
Dual Codebook VQ: Enhanced Image Reconstruction with Reduced Codebook Size
Parisa Boodaghi Malidarreh, Jillur Rahman Saurav, Thuong Le Hoai Pham +5
Vector Quantization (VQ) techniques face significant challenges in codebook utilization, limiting reconstruction fidelity in image modeling. We introduce a Dual Codebook mechanism…
Peptide Sequencing Via Protein Language Models
Thuong Le Hoai Pham, Jillur Rahman Saurav, Aisosa A. Omere +9
We introduce a protein language model for determining the complete sequence of a peptide based on measurement of a limited set of amino acids. To date, protein sequencing relies on…
Real-Time Diagnostic Integrity Meets Efficiency: A Novel Platform-Agnostic Architecture for Physiological Signal Compression
Neel R Vora, Amir Hajighasemi, Cody T. Reynolds +16
Head-based signals such as EEG, EMG, EOG, and ECG collected by wearable systems will play a pivotal role in clinical diagnosis, monitoring, and treatment of important brain disorde…
SpatialVisVR: An Immersive, Multiplexed Medical Image Viewer With Contextual Similar-Patient Search
Jai Prakash Veerla, Partha Sai Guttikonda, Amir Hajighasemi +7
In contemporary pathology, multiplexed immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) present both significant opportunities and challenges. These methodologies…
Predicting Future States with Spatial Point Processes in Single Molecule Resolution Spatial Transcriptomics
Biraaj Rout, Priyanshi Borad, Parisa Boodaghi Malidarreh +6
In this paper, we introduce a pipeline based on XGboost to predict the future distribution of cells that are expressed by the Sog-D gene (active cells) in both the Anterior to post…
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…
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…
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…