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Author Archives: Cristian Badea
QIAL Perspective
239 steps up Duke Chapel with the QIAL team! Worth it for the view, the reset, and the reminder to step back and see the bigger picture.
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QIAL Celebrates a PhD Milestone
Congratulations to Dr. Rohan Nadkarni on successfully defending his PhD today. We are proud of all his hard work and contributions in the QIAL lab, and we wish him the very best ahead.
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Predictive Alzheimer’s Risk
Congratulations to QIAL’s Dr. Alexandra Badea and Dr. Trong-Kha Truong on receiving the 2025 Medical Physics Fall Seed Grant Award for their project, “Predictive Modeling of Alzheimer’s Disease Risk Using Explainable AI and High-Resolution MRI.”
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Exercise Protects the Aging Heart in High-Fat Diet APOE Mice
Using photon-counting CT and deep learning, we show that voluntary exercise significantly mitigates high-fat diet–induced cardiac dysfunction in adult APOE-targeted mice, with the strongest benefits observed in APOE4 and humanized innate immune (HN) backgrounds. Exercise mitigates high-fat diet–induced cardiac dysfunction … Continue reading
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Imaging Bone Aging with Photon-Counting CT
How do genetics, sex, and immune signaling shape bone health as mice age?Our study shows that photon-counting CT in APOE mouse models reveals strong sex- and immune-dependent bone loss, with female HN mice showing the most pronounced decline. Nadkarni, R.; … Continue reading
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Visiting Fulbright Scholar: Dr Kristina Bliznakova
Delighted to host Dr. Kristina Bliznakova, Fulbright Scholar, at Duke’s Quantitative Imaging & Analysis Lab. Looking forward to teaming up on photon-counting CT and virtual imaging.
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Identifying Alzheimer’s network biomarkers
New article and three institutions collaborating! We identify network biomarkers of Alzheimer’s risk by combining high-res MRI with multifactorial analysis in ApoE mouse models. Joint volume + texture patterns reveal how genotype, sex, diet, & immunity interact to shape brain … Continue reading
Virtual Wistar Rats Enable Realistic PCCT Simulations
Our team developed anatomically variable digital Wistar rat phantoms for realistic preclinical imaging simulations, enabling PCCT studies & reducing animal use. Segars, H. E., Nadkarni, R., Badea, C. T., Badea, A., Chin, B., Johnson, G. A., Payne, J., Samei, E., … Continue reading
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Olfactory-Guided Behavior Uncovers Signatures of AD risk
Could your sense of smell reveal Alzheimer’s risk years before memory loss? Our new study connects olfactory behavior, brain networks, & blood gene signatures to early AD vulnerability. Moon, H.S.; Han, Z.Y.; Anderson, R.J.; Mahzarnia, A.; Stout, J.A.; Niculescu, A.R.; Tremblay, J.T.; … Continue reading
Adaptive AI Denoising for Pediatric Cardiac PCCT
We developed a data-adaptive, self-supervised deep learning method combining sparse coding (SC) + visual transformer (ViT) for denoising pediatric cardiac photon-counting CT. Preserves anatomy, adapts to noise, generalizes well—even to preclinical data. Clark, D. P., Cao, J. Y., & Badea, … Continue reading
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