Arianna Bunnell

Computer Science PhD Student

I am studying for a Ph.D. in Computer Science in the Department of Information and Computer Sciences at the University of Hawaii at Manoa. My research interests are in deep learning for breast imaging, specifically in breast ultrasound. I'm also passionate about the study of healthcare AI ethics, particularly under feminist and intersectional frameworks.

Papers

Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging

Arianna Bunnell et al. (2025) In International Workshop on Shape in Medical Imaging, Daejeon, Republic of Korea.

Full Article

Artificial intelligence-enhanced handheld breast ultrasound for screening: A systematic review of diagnostic test accuracy

Arianna Bunnell et al. (2025) PLOS Digital Health, 4(9), e0001019.

Full Article

Prediction of mammographic breast density based on clinical breast ultrasound images using deep learning: a retrospective analysis

Arianna Bunnell et al. (2025) The Lancet Regional Health - Americas (46): ISSN 2667-193X.

Full Article

BUSClean: Open-source software for breast ultrasound image pre-processing and knowledge extraction for medical AI

Arianna Bunnell, Kailee Hung et al. (2024) PLOS ONE 19(12): e0315434.

Full Article

Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound

Arianna Bunnell et al. (2024) 27th International Conference on Medical Image Computing and Computer Assisted Intervention, Marrakesh, Morocco.

Full Article

Early Breast Cancer Diagnosis via Breast Ultrasound and Deep Learning

Arianna Bunnell (2023) Master’s Thesis, University of Hawaii at Manoa.

Full Article

See all 7 papers

Presentations

Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging 2025

I presented my work in a poster on using deep learning to place fiducial points to enable statistical shape and appearance modeling to discover body shape phentoypes at the ShapeMI Workshop at MICCAI 2025.

Poster DXA AI

Concept Bottleneck Models with Expert Ontologies for the Diagnosis of Cancer from Medical Imaging 2025

I defended my dissertation proposal in November 2025! Pictured is my committee (left to right): Dr. Tai Maaz, myself, Dr. George Chen, Dr. Peter Sadowski, Dr. John Shepherd, and Dr. Kim Binsted (not pictured).

Cancer Oral XAI

Mammography AI Models and Radiomic Features for Breast Cancer Risk Prediction: A Matched Case-Control Study in an Ethnically-Diverse Cohort 2025

I presented my work on evaluation of existing AI and radiomic markers from mammography for breast cancer risk assessment in ANHPI women at the International Breast Density Workshop in Līhuʻe.

Poster Oral Breast Cancer AI