Examination of chest X-ray images is currently one of the most important methods for the
screening and diagnosis of thoracic diseases and, in some cases, for assessing response to …

In computer-aided drug discovery (CADD), virtual screening (VS) is used for comparing a
library of compounds against known active ligands to identify the drug candidates that are …

Topological data analysis (TDA) is gaining prominence across a wide spectrum of machine
learning tasks that spans from manifold learning to graph classification. A pivotal technique …

The efficacy of segmentation algorithms is frequently compromised by topological errors like
overlapping regions, disrupted connections, and voids. To tackle this problem, we introduce …

The analysis of fundus images for the early screening of eye diseases is of great clinical
importance. Traditional methods for such analysis are time-consuming and expensive as it …

Topological data analysis (TDA) delivers invaluable and complementary information on the
intrinsic properties of data inaccessible to conventional methods. However, high …

We present a transformative approach to histopathological cancer detection and grading by
introducing a very powerful feature extraction method based on the latest topological data …

Stopping power ratio (SPR) maps are needed for dose deposition calculations and are
typically estimated from single energy CT (SECT) in clinical routine. SECT-based SPR …

In this paper, we bring a new perspective to persistent homology by incorporating key
concepts from metric geometry. For a given compact subset $ X $ of a Banach space $ Y …

In this paper, we introduce a novel approach that utilizes topological data analysis (TDA) in
conjunction with MRI for determining glioma grade and identifying genomic biomarkers. The …