2 citations · 3 across the 18 of their papers we have counts for
18 papers
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski +4
Diffusion models are prone to generating structural hallucinations - samples that match the statistical properties of the training data yet defy underlying structural rules, result…
Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions
Bartlomiej Sobieski, Jakub Grzywaczewski, Karol Dobiczek +6
Lung cancer remains the leading cause of cancer mortality, driving the development of automated screening tools to alleviate radiologist workload. Standing at the frontier of this…
BioNIC: Biologically Inspired Neural Network for Image Classification Using Connectomics Principles
Diya Prasanth, Matthew Tivnan
We present BioNIC, a multi-layer feedforward neural network for emotion classification, inspired by detailed synaptic connectivity graphs from the MICrONs dataset. At a structural…
Projection Embedded Diffusion Bridge for CT Reconstruction from Incomplete Data
Yuang Wang, Pengfei Jin, Siyeop Yoon +6
Reconstructing CT images from incomplete projection data remains challenging due to the ill-posed nature of the problem. Diffusion bridge models have recently shown promise in rest…
System-Embedded Diffusion Bridge Models
Bartlomiej Sobieski, Matthew Tivnan, Yuang Wang +5
Solving inverse problems -- recovering signals from incomplete or noisy measurements -- is fundamental in science and engineering. Score-based generative models (SGMs) have recentl…
Surf2CT: Cascaded 3D Flow Matching Models for Torso 3D CT Synthesis from Skin Surface
Siyeop Yoon, Yujin Oh, Pengfei Jin +5
We present Surf2CT, a novel cascaded flow matching framework that synthesizes full 3D computed tomography (CT) volumes of the human torso from external surface scans and simple dem…
Cascaded 3D Diffusion Models for Whole-body 3D 18-F FDG PET/CT synthesis from Demographics
Siyeop Yoon, Sifan Song, Pengfei Jin +6
We propose a cascaded 3D diffusion model framework to synthesize high-fidelity 3D PET/CT volumes directly from demographic variables, addressing the growing need for realistic digi…
OWT: A Foundational Organ-Wise Tokenization Framework for Medical Imaging
Sifan Song, Siyeop Yoon, Pengfei Jin +10
Recent advances in representation learning often rely on holistic embeddings that entangle multiple semantic components, limiting interpretability and generalization. These issues…
Prediction of Frozen Region Growth in Kidney Cryoablation Intervention Using a 3D Flow-Matching Model
Siyeop Yoon, Yujin Oh, Matthew Tivnan +7
This study presents a 3D flow-matching model designed to predict the progression of the frozen region (iceball) during kidney cryoablation. Precise intraoperative guidance is criti…
Pseudoinverse Diffusion Models for Generative CT Image Reconstruction from Low Dose Data
Matthew Tivnan, Dufan Wu, Quanzheng Li
Score-based diffusion models have significantly advanced generative deep learning for image processing. Measurement conditioned models have also been applied to inverse problems su…
Multi-Source Static CT with Adaptive Fluence Modulation to Minimize Hallucinations in Generative Reconstructions
Matthew Tivnan, Amar Gupta, Kai Yang +2
Multi-source static Computed Tomography (CT) systems have introduced novel opportunities for adaptive imaging techniques. This work presents an innovative method of fluence field m…
Generative Super-Resolution PET Imaging with Fourier Diffusion Models
Matthew Tivnan, Quanzheng Li
Neurological Positron Emission Tomography (PET) is a critical imaging modality for diagnosing and studying neurodegenerative diseases like Alzheimer's disease. However, the inheren…
Rethinking Visual Counterfactual Explanations Through Region Constraint
Bartlomiej Sobieski, Jakub Grzywaczewski, Bartlomiej Sadlej +2
Visual counterfactual explanations (VCEs) have recently gained immense popularity as a tool for clarifying the decision-making process of image classifiers. This trend is largely m…
Volumetric Conditional Score-based Residual Diffusion Model for PET/MR Denoising
Siyeop Yoon, Rui Hu, Yuang Wang +6
PET imaging is a powerful modality offering quantitative assessments of molecular and physiological processes. The necessity for PET denoising arises from the intrinsic high noise…
Hallucination Index: An Image Quality Metric for Generative Reconstruction Models
Matthew Tivnan, Siyeop Yoon, Zhennong Chen +3
Generative image reconstruction algorithms such as measurement conditioned diffusion models are increasingly popular in the field of medical imaging. These powerful models can tran…
Measurement Embedded Schrödinger Bridge for Inverse Problems
Yuang Wang, Pengfei Jin, Siyeop Yoon +4
Score-based diffusion models are frequently employed as structural priors in inverse problems. However, their iterative denoising process, initiated from Gaussian noise, often resu…
Conditional Score-Based Diffusion Model for Cortical Thickness Trajectory Prediction
Qing Xiao, Siyeop Yoon, Hui Ren +6
Alzheimer's Disease (AD) is a neurodegenerative condition characterized by diverse progression rates among individuals, with changes in cortical thickness (CTh) closely linked to i…
Implicit Image-to-Image Schrodinger Bridge for Image Restoration
Yuang Wang, Siyeop Yoon, Pengfei Jin +8
Diffusion-based models have demonstrated remarkable effectiveness in image restoration tasks; however, their iterative denoising process, which starts from Gaussian noise, often le…