399 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Rice UniversityUS17 papers
- The University of Texas Health Science Center at HoustonUS17 papers
- The University of Texas at AustinUS13 papers
- Harvard UniversityUS12 papers
- Baylor College of MedicineUS10 papers
- The University of Texas Southwestern Medical CenterUS9 papers
- University of PennsylvaniaUS8 papers
- Massachusetts General HospitalUS7 papers
- Stanford UniversityUS7 papers
- Technical University of MunichDE7 papers
- University of Alabama at BirminghamUS7 papers
- University of North Carolina at Chapel HillUS7 papers
16 papers · 1 filter
Dosimetric calibration of an anatomically specific ultra-high dose rate electron irradiation platform for preclinical FLASH radiobiology experiments
Jinghui Wang, Stavros Melemenidis, Rakesh Manjappa +16
We characterized the dosimetric properties of a clinical linear accelerator configured to deliver ultra-high dose rate (UHDR) irradiation to mice and cell-culture FLASH radiobiolog…
Dynamic CBCT Imaging using Prior Model-Free Spatiotemporal Implicit Neural Representation (PMF-STINR)
Hua-Chieh Shao, Mengke Tielige, Tinsu Pan +1
Dynamic cone-beam computed tomography (CBCT) can capture high-spatial-resolution, time-varying images for motion monitoring, patient setup, and adaptive planning of radiotherapy. H…
A reluctant additive model framework for interpretable nonlinear individualized treatment rules
Jacob M. Maronge, Jared D. Huling, Guanhua Chen
Individualized treatment rules (ITRs) for treatment recommendation is an important topic for precision medicine as not all beneficial treatments work well for all individuals. Inte…
Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend
McKell Woodland, Austin Castelo, Mais Al Taie +8
Fréchet Inception Distance (FID) is a widely used metric for assessing synthetic image quality. It relies on an ImageNet-based feature extractor, making its applicability to medica…
Forum on immune digital twins: a meeting report
Reinhard Laubenbacher, Fred Adler, Gary An +16
Medical digital twins are computational models of human biology relevant to a given medical condition, which can be tailored to an individual patient, thereby predicting the course…
Evolving Horizons in Radiotherapy Auto-Contouring: Distilling Insights, Embracing Data-Centric Frameworks, and Moving Beyond Geometric Quantification
Kareem A. Wahid, Carlos E. Cardenas, Barbara Marquez +8
Deep learning has significantly advanced the potential for automated contouring in radiotherapy planning. In this manuscript, guided by contemporary literature, we underscore three…
Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
Chen Zhao, Kuan-Jui Su, Chong Wu +13
Background: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing…
Separable effects for adherence
Kerollos Nashat Wanis, Mats Julius Stensrud, Aaron Leor Sarvet
Comparing different medications is complicated when adherence to these medications differs. We can overcome the adherence issue by assessing effectiveness under sustained use, as i…
Text Classification of Cancer Clinical Trial Eligibility Criteria
Yumeng Yang, Soumya Jayaraj, Ethan B Ludmir +1
Automatic identification of clinical trials for which a patient is eligible is complicated by the fact that trial eligibility is stated in natural language. A potential solution to…
Current Methods for Hyperpolarized [1-13C]pyruvate MRI Human Studies
Peder EZ Larson, Jenna ML Bernard, James A Bankson +16
MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney dise…
Predictive Digital Twin for Optimizing Patient-Specific Radiotherapy Regimens under Uncertainty in High-Grade Gliomas
Anirban Chaudhuri, Graham Pash, David A. Hormuth +6
We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipa…
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation
McKell Woodland, Nihil Patel, Mais Al Taie +4
Clinically deployed segmentation models are known to fail on data outside of their training distribution. As these models perform well on most cases, it is imperative to detect out…
Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Rapid Multiparametric Quantitative MRI Using 3D-QALAS
Yohan Jun, Yamin Arefeen, Jaejin Cho +7
Purpose: To develop and evaluate methods for 1) reconstructing 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) time-ser…
Overlapping Indices for Dynamic Information Borrowing in Bayesian Hierarchical Modeling
Xuetao Lu, J. Jack Lee
Bayesian hierarchical model (BHM) has been widely used in synthesizing information across subgroups. Identifying heterogeneity in the data and determining proper strength of borrow…
Community-developed checklists for publishing images and image analysis
Christopher Schmied, Michael Nelson, Sergiy Avilov +51
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. H…
Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes
Kareem Allam, Xiaohong Iris Wang, Songlin Zhang +6
Deep learning has been shown to be useful to detect breast cancer metastases by analyzing whole slide images of sentinel lymph nodes. However, it requires extensive scanning and an…