December, 2022

Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography.

Dec. 2, 2022—Thomas Z. Li, Kaiwen Xu, Riqiang Gao, Yucheng Tang, Thomas A. Lasko, Fabien Maldonado, Kim Sandler, Bennett A. Landman. Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography. SPIE Medical Imaging 2022. Full text: arxiv.org/abs/2209.01676 Abstract Features learned from single radiologic images are unable to provide information about whether and how much a lesion...

UMAP of the normalized histogram representation of WSI neutrophil density for the entire dataset. All patches in this figure depict the 256 × 256 pixel CLAM patch with the maximum neutrophil density from the corresponding WSI. The UMAP displayed with patches depicts more clearly visible crypts and tissue edges in the normal cluster max patches than the active disease cluster (A). The UMAP displayed with circle markers highlights the separability of the two classes (B). Example patches are shown with their predicted neutrophil segmentation in green (C, D, E, F). Looking deep into the normal cluster, expected patches (C) and active disease outliers (D) show tissue edges and few segmented neutrophils. In the active disease cluster, expected patches (E) and normal tissue CD outliers (F) both show a larger number of segmented neutrophils, with fewer tissue edges visible (F).

Predicting Crohn’s disease severity in the colon using mixed cell nucleus density from pseudo labels

Dec. 1, 2022—Lucas W. Remedios, Shunxing Bao, Cailey I. Kerley, Leon Y. Cai, François Rheault, Ruining Deng, Can Cui, Sophie Chiron, Ken S. Lau, Joseph T. Roland, Mary K. Washington, Lori A. Coburn, Keith T. Wilson, Yuankai Huo, Bennett A. Landman (2023). Predicting Crohn’s disease severity in the colon using mixed cell nucleus density from pseudo labels....