The State of Applying Artificial Intelligence to Tissue Imaging for Cancer Research and Early Detection

no code implementations • 29 Jun 2023 • Michael Robben, Amir Hajighasemi, Mohammad Sadegh Nasr, Jai Prakesh Veerla, Anne M. Alsup, Biraaj Rout, Helen H. Shang, Kelli Fowlds, Parisa Boodaghi Malidarreh, Paul Koomey, MD Jillur Rahman Saurav, Jacob M. Luber

Artificial intelligence represents a new frontier in human medicine that could save more lives and reduce the costs, thereby increasing accessibility.

Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image Compression

1 code implementation • 23 Mar 2023 • Mohammad Sadegh Nasr, Amir Hajighasemi, Paul Koomey, Parisa Boodaghi Malidarreh, Michael Robben, Jillur Rahman Saurav, Helen H. Shang, Manfred Huber, Jacob M. Luber

We generate and visualize embeddings from the compressed latent space and demonstrate how they are useful for clinical interpretation of data, and how in the future such latent embeddings can be used to accelerate search of clinical imaging data.

Image Compression

A SSIM Guided cGAN Architecture For Clinically Driven Generative Image Synthesis of Multiplexed Spatial Proteomics Channels

2 code implementations • 20 May 2022 • Jillur Rahman Saurav, Mohammad Sadegh Nasr, Paul Koomey, Michael Robben, Manfred Huber, Jon Weidanz, Bríd Ryan, Eytan Ruppin, Peng Jiang, Jacob M. Luber

We validate these claims by generating a new experimental spatial proteomics data set from human lung adenocarcinoma tissue sections and show that a model trained on HuBMAP can accurately synthesize channels from our new data set.

Ethics Generative Adversarial Network +2