output
20132025
most citedMachine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

693 citations

28 papers

physics.med-ph2025

Geometric and Dosimetric Validation of Deformable Image Registration for Prostate MR-guided Adaptive Radiotherapy

Victor N. Malkov, Iymad R. Mansour, Vickie Kong +8

Objective: Quantify geometric and dosimetric accuracy of a novel prostate MR-to-MR deformable image registration (DIR) approach to support MR-guided adaptive radiation therapy dose…

eess.IV2023★ 151 cited

The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

Jun Ma, Ronald Xie, Shamini Ayyadhury +37

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…

cs.CV2023★ 204 cited

Understanding metric-related pitfalls in image analysis validation

Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…

cs.CV2022★ 469 cited

Metrics reloaded: Recommendations for image analysis validation

Lena Maier-Hein, Annika Reinke, Patrick Godau +71

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…

physics.med-ph2022★ 13 cited

Modeling the impact of spatial oxygen heterogeneity on radiolytic oxygen depletion during FLASH radiotherapy

Edward Taylor, Richard P. Hill, Daniel Letourneau

It has been postulated that the delivery of radiotherapy at ultra-high dose rates ("FLASH") reduces normal tissue toxicities by depleting them of oxygen. The fraction of normal tis…

eess.SY2022★ 1 cited

Information-theoretic multi-time-scale partially observable systems with inspiration from leukemia treatment

Margaret P. Chapman, Emily Jensen, Steven M. Chan +1

We study a partially observable nonlinear stochastic system with unknown parameters, where the given time scales of the states and measurements may be distinct. The proposed settin…