Analysis/AI
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The goal of the Image Analysis/AI Interest Group of the Yale Biomedical Imaging Institute is to promote AI/image analysis research in the Yale School of Medicine. The group consists of faculty and trainees who are interested in this area, either as developers of new algorithms/software or as users of these types of methods for their research.
We have two primary activities. The first is a set of bi-weekly training sessions on a particular practical imaging analysis task. Recordings of previous sessions are available to group members on the IAAI SharePoint. If you cannot access the shared drive, please request access using the contact information below.
The second activity is to provide office hours for imaging analysis consultation to YSM researchers. If you are interested, please fill in the form below and one of us will reach out to you.
Interested in collaborating?
This is an informal group, and anyone at Yale is welcome to attend our events. We advertise these (plus relevant other talks at Yale) on our email list. To subscribe, please sign up here.
The group is led by a steering committee consisting of (in alphabetical order) Nicha Dvornek, Thibault Marin, John Onofrey, Xenios Papademetris, and Dustin Scheinost.
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YBII AI Papers
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2025
Physics-Informed List-Mode Deep Image Prior Reconstruction with Motion Correction in 3D Brain PET
Chemli Y, Najmaoui Y, Normandin M, Fakhri G, Marin T, Ouyang J. Physics-Informed List-Mode Deep Image Prior Reconstruction with Motion Correction in 3D Brain PET. 2021 IEEE Nuclear Science Symposium And Medical Imaging Conference (NSS/MIC) 2025, 1-2. DOI: 10.1109/nss/mic/rtsd57106.2025.11287851.
Kalluvila A, Wang E, Hurley M, Freeman C, Johnson J. Radiologist-Validated Automatic Lumbar T1-Weighted Spinal MRI Segmentation Tool via an Attention U-Net Algorithm. Diagnostics 2025, 15: 3046. PMID: 41374427, PMCID: PMC12691307, DOI: 10.3390/diagnostics15233046.
PET Head Motion Estimation Using Supervised Deep Learning with Attention
Cai Z, Zeng T, Zhang J, Lieffrig E, Fontaine K, You C, Revilla E, Duncan J, Xin J, Lu Y, Onofrey J. PET Head Motion Estimation Using Supervised Deep Learning with Attention. IEEE Transactions On Medical Imaging 2025, PP: 1-1. PMID: 41082441, DOI: 10.1109/tmi.2025.3620714.
Xia M, Xie H, Liu Q, Zhou B, Wang H, Li B, Rominger A, Li Q, Badawi R, Shi K, Fakhri G, Liu C. LeqMod: Adaptable Lesion-Quantification-Consistent Modulation for Deep Learning Low-Count PET Image Denoising. IEEE Transactions On Medical Imaging 2025, PP: 1-1. PMID: 41052161, DOI: 10.1109/tmi.2025.3618247.
Geometry-Guided Local Alignment for Multi-view Visual Language Pre-training in Mammography
Du Y, Chen L, Dvornek N. Geometry-Guided Local Alignment for Multi-view Visual Language Pre-training in Mammography. Lecture Notes In Computer Science 2025, 15965: 299-310. DOI: 10.1007/978-3-032-04978-0_29.
Guo L, Liu C, Soultanidis G. Motion Management in Positron Emission Tomography/Computed Tomography and Positron Emission Tomography/Magnetic Resonance. PET Clinics 2025, 20: 423-437. PMID: 40858422, DOI: 10.1016/j.cpet.2025.07.004.
A generalizable diffusion framework for 3D low-dose and few-view cardiac SPECT imaging
Xie H, Gan W, Ji W, Chen X, Alashi A, Thorn S, Zhou B, Liu Q, Xia M, Guo X, Liu Y, An H, Kamilov U, Wang G, Sinusas A, Liu C. A generalizable diffusion framework for 3D low-dose and few-view cardiac SPECT imaging. Medical Image Analysis 2025, 106: 103729. PMID: 40752375, PMCID: PMC12360895, DOI: 10.1016/j.media.2025.103729.
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models. IEEE Transactions On Medical Imaging 2025, 44: 5089-5102. PMID: 40663684, PMCID: PMC12318411, DOI: 10.1109/tmi.2025.3588859.
Using Foundation Models as Pseudo-label Generators for Pre-clinical 4D Cardiac CT Segmentation
Rickmann A, Thorn S, Ahn S, Lee S, Uman S, Lysyy T, Burns R, Guerrera N, Spinale F, Burdick J, Sinusas A, Duncan J. Using Foundation Models as Pseudo-label Generators for Pre-clinical 4D Cardiac CT Segmentation. Lecture Notes In Computer Science 2025, 15673: 253-265. DOI: 10.1007/978-3-031-94562-5_23.
Chen T, Hou J, Zhou Y, Xie H, Chen X, Liu Q, Guo X, Xia M, Duncan J, Liu C, Zhou B. 2.5D Multi-View Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-Count PET Reconstruction With CT-Less Attenuation Correction. IEEE Transactions On Medical Imaging 2025, 44: 4239-4250. PMID: 40372846, PMCID: PMC12632186, DOI: 10.1109/tmi.2025.3570342.
An Investigation on Cross-Tracer Generalizability of Deep Learning-Based PET Attenuation Correction
Hou J, Chen T, Zhou Y, Chen X, Xie H, Liu Q, Xia M, Panin V, Toyonaga T, Liu C, Zhou B. An Investigation on Cross-Tracer Generalizability of Deep Learning-Based PET Attenuation Correction. IEEE Transactions On Radiation And Plasma Medical Sciences 2025, 9: 1025-1035. PMID: 41221103, PMCID: PMC12599847, DOI: 10.1109/trpms.2025.3566630.
Causal Modeling of FMRI Time-Series for Interpretable Autism Spectrum Disorder Classification
Duan P, Dvornek N, Wang J, Staib L, Duncan J. Causal Modeling of FMRI Time-Series for Interpretable Autism Spectrum Disorder Classification. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10980933.
Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning
Zheng X, Worhunsky P, Liu Q, Guo X, Chen X, Sun H, Zhang J, Toyonaga T, Mecca A, O’Dell R, van Dyck C, Angarita G, Cosgrove K, D’Souza D, Matuskey D, Esterlis I, Carson R, Radhakrishnan R, Liu C. Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning. EJNMMI Physics 2025, 12: 30. PMID: 40163154, PMCID: PMC11958861, DOI: 10.1186/s40658-025-00744-5.
Xie H, Alashi A, Thorn S, Chen X, Zhou B, Sinusas A, Liu C. Increasing angular sampling for dedicated cardiac single photon emission computed tomography scanner: Implementation with deep learning and validation with human data. Journal Of Nuclear Cardiology 2025, 49: 102168. PMID: 39986346, PMCID: PMC12227299, DOI: 10.1016/j.nuclcard.2025.102168.
Barrientos L, Gonzales R, Lamy J, Seemann F, Mojibian H, Heerdt P, Singh I, Peters D. Deep learning-based measurement of isovolumic relaxation time from cardiovascular magnetic resonance long-axis cines: Validation with pressure-derived IVRT. Journal Of Cardiovascular Magnetic Resonance 2025, 27: 101286. DOI: 10.1016/j.jocmr.2024.101286.
2024
Xie H, Gan W, Chen X, Zhou B, Liu Q, Xia M, Guo X, Liu Y, An H, Kamilov U, Wang G, Sinusas A, Liu C. Dose-aware Diffusion Model for 3D Low-count Cardiac SPECT Image Denoising with Projection-domain Consistency. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10655170.
Guo X, Tsai Y, Liu Q, Guo L, Valadez G, Dvornek N, Liu C. Deep Learning-based Dynamic PET Intra-frame Motion Correction and Integration with Inter-frame Motion Estimation. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657268.
Diffusion-based Bayesian posterior distribution prediction of kinetic parameters in dynamic PET
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Diffusion-based Bayesian posterior distribution prediction of kinetic parameters in dynamic PET. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657955.
Anatomically and Metabolically Informed Deep Learning Low-Count PET Image Denoising
Xia M, Xie H, Liu Q, Guo L, Ouyang J, Bayerlein R, Spencer B, Badawi R, Li Q, Fakhri G, Liu C. Anatomically and Metabolically Informed Deep Learning Low-Count PET Image Denoising. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10657099.
An Investigation on Cross-Tracer Generalizability of Deep Learning-based PET Attenuation Correction
Hou J, Chen T, Zhou Y, Chen X, Xie H, Liu Q, Xia M, Panin V, Liu C, Zhou B, Toyonaga T. An Investigation on Cross-Tracer Generalizability of Deep Learning-based PET Attenuation Correction. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657095.
Liang Q, Adkinson B, Jiang R, Scheinost D. Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling. Lecture Notes In Computer Science 2024, 15010: 579-588. DOI: 10.1007/978-3-031-72117-5_54.
Dong S, Cai Z, Hangel G, Bogner W, Widhalm G, Huang Y, Liang Q, You C, Kumaragamage C, Fulbright R, Mahajan A, Karbasi A, Onofrey J, de Graaf R, Duncan J. A Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging. Medical Image Analysis 2024, 99: 103358. PMID: 39353335, PMCID: PMC11609020, DOI: 10.1016/j.media.2024.103358.
Subject-aware PET Denoising with Contrastive Adversarial Domain Generalization
Liu X, Marin T, Eslahi S, Tiss A, Chemli Y, Johson K, Fakhri G, Ouyang J. Subject-aware PET Denoising with Contrastive Adversarial Domain Generalization. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-1. PMID: 39445307, PMCID: PMC11497478, DOI: 10.1109/nss/mic/rtsd57108.2024.10656150.
Lamy J, Gonzales R, Xiang J, Seemann F, Huber S, Steele J, Wieben O, Heiberg E, Peters D. Tricuspid valve flow measurement using a deep learning framework for automated valve‐tracking 2D phase contrast. Magnetic Resonance In Medicine 2024, 92: 1838-1850. PMID: 38817154, PMCID: PMC11341256, DOI: 10.1002/mrm.30163.
Lee W, Zhuo Y, Marin T, Han P, Chi D, El Fakhri G, Ma C. A deep learning-based approach to nuisance signal removal from MRSI data asquired without suppression. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/0259.
Liu Q, Tsai Y, Gallezot J, Guo X, Chen M, Pucar D, Young C, Panin V, Casey M, Miao T, Xie H, Chen X, Zhou B, Carson R, Liu C. Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification. Medical Image Analysis 2024, 95: 103180. PMID: 38657423, DOI: 10.1016/j.media.2024.103180.
Cross noise level PET denoising with continuous adversarial domain generalization
Liu X, Eslahi S, Marin T, Tiss A, Chemli Y, Huang Y, Johnson K, Fakhri G, Ouyang J. Cross noise level PET denoising with continuous adversarial domain generalization. Physics In Medicine And Biology 2024, 69: 085001. PMID: 38484401, PMCID: PMC11195012, DOI: 10.1088/1361-6560/ad341a.
Dong S, Shewarega A, Chapiro J, Cai Z, Hyder F, Coman D, Duncan J. High‐resolution extracellular pH imaging of liver cancer with multiparametric MR using Deep Image Prior. NMR In Biomedicine 2024, 37: e5145. PMID: 38488205, DOI: 10.1002/nbm.5145.
2023
Unified Noise-Aware Network for Low-Count PET Denoising With Varying Count Levels
Xie H, Liu Q, Zhou B, Chen X, Guo X, Wang H, Li B, Rominger A, Shi K, Liu C. Unified Noise-Aware Network for Low-Count PET Denoising With Varying Count Levels. IEEE Transactions On Radiation And Plasma Medical Sciences 2023, 8: 366-378. PMID: 39391291, PMCID: PMC11463975, DOI: 10.1109/trpms.2023.3334105.
Fast Reconstruction Enhances Deep Learning PET Head Motion Correction
Zeng T, Chen F, Zhang J, Lieffrig E, Cai Z, Naganawa M, You C, Lu Y, Onofrey J. Fast Reconstruction Enhances Deep Learning PET Head Motion Correction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338189
Teacher’s PET: Semi-supervised Deep Learning for PET Head Motion Correction
Zeng T, You C, Cai Z, Lieffrig E, Zhang J, Chen F, Lu Y, Onofrey J. Teacher’s PET: Semi-supervised Deep Learning for PET Head Motion Correction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10337834.
Image Intensity Normalization Benefits Deep Learning Brain PET Motion Correction
Lieffrig E, Zhang J, Zeng T, Cai Z, You C, Lu Y, Onofrey J. Image Intensity Normalization Benefits Deep Learning Brain PET Motion Correction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338194.
Spatial Normalization to Improve Deep Learning-based Head Motion Correction in PET
Zhang J, Lieffrig E, Zeng T, You C, Cai Z, Toyonaga T, Lu Y, Onofrey J. Spatial Normalization to Improve Deep Learning-based Head Motion Correction in PET. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338387.
Zhou B, Zhou B, Xie H, Liu Q, Chen X, Guo X, Zhou K, Li B, Rominger A, Shi K, Duncan J, Liu C. FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338446.
Chen X, Zhou B, Xie H, Guo X, Liu Q, Sinusas A, Liu C. Cross-Domain Iterative Network for Simultaneous Denoising, Limited-Angle Reconstruction, and Attenuation Correction of Cardiac SPECT. Lecture Notes In Computer Science 2023, 14348: 12-22. DOI: 10.1007/978-3-031-45673-2_2.
Zhou B, Xie H, Liu Q, Chen X, Guo X, Feng Z, Hou J, Zhou S, Li B, Rominger A, Shi K, Duncan J, Liu C. FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising. Medical Image Analysis 2023, 90: 102993. PMID: 37827110, PMCID: PMC10611438, DOI: 10.1016/j.media.2023.102993.
Guo X, Zhou B, Chen X, Chen M, Liu C, Dvornek N. MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction. IEEE Transactions On Medical Imaging 2023, 42: 3512-3523. PMID: 37368811, PMCID: PMC10751388, DOI: 10.1109/tmi.2023.3290003.
Zhou B, Tsai Y, Zhang J, Guo X, Xie H, Chen X, Miao T, Lu Y, Duncan J, Liu C. Fast-MC-PET: A Novel Deep Learning-Aided Motion Correction and Reconstruction Framework for Accelerated PET. Lecture Notes In Computer Science 2023, 13939: 523-535. DOI: 10.1007/978-3-031-34048-2_40.
Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation
Huang Y, Xie W, Li M, Cheng M, Wu J, Wang W, You J, Liu X. Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation. Lecture Notes In Computer Science 2023, 13939: 360-371. DOI: 10.1007/978-3-031-34048-2_28.
Baloescu C, Chen A, Varasteh A, Toporek G, McNamara R, Raju B, Moore C. Two‐ Versus 8‐Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm. Journal Of Ultrasound In Medicine 2023, 42: 2349-2356. PMID: 37255051, DOI: 10.1002/jum.16262.
SVD Compression for Nonlinear Encoding Imaging with Model-based Deep Learning Reconstruction
Zhang Z, Selvaganesan K, Ha Y, Sun C, Samardzija A, Sun H, Galiana G, Constable R. SVD Compression for Nonlinear Encoding Imaging with Model-based Deep Learning Reconstruction. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2023 DOI: 10.58530/2023/0833.
Chen X, Zhou B, Xie H, Guo X, Zhang J, Duncan J, Miller E, Sinusas A, Onofrey J, Liu C. DuSFE: Dual-Channel Squeeze-Fusion-Excitation co-attention for cross-modality registration of cardiac SPECT and CT. Medical Image Analysis 2023, 88: 102840. PMID: 37216735, PMCID: PMC10524650, DOI: 10.1016/j.media.2023.102840.
Kucukkaya A, Zeevi T, Chai N, Raju R, Haider S, Elbanan M, Petukhova-Greenstein A, Lin M, Onofrey J, Nowak M, Cooper K, Thomas E, Santana J, Gebauer B, Mulligan D, Staib L, Batra R, Chapiro J. Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning. Scientific Reports 2023, 13: 7579. PMID: 37165035, PMCID: PMC10172370, DOI: 10.1038/s41598-023-34439-7.
Explainable AI for Prostate MRI: Don't Trust, Verify.
Chapiro J. Explainable AI for Prostate MRI: Don't Trust, Verify. Radiology 2023, 307: e230574. PMID: 37039689, PMCID: PMC10323286, DOI: 10.1148/radiol.230574.
Miao T, Tsai Y, Zhou B, Menard D, Schleyer P, Hong I, Casey M, Liu C. Direct respiratory motion correction of whole-body PET images using a deep learning framework incorporating spatial information. Progress In Biomedical Optics And Imaging 2023, 12463: 124633x-124633x-9. DOI: 10.1117/12.2654472.
Zhong J, Staib L, Venkataraman R, Onofrey J. Integrating Prostate Specific Antigen Density Biomarker Into Deep Learning Prostate MRI Lesion Segmentation Models. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38090633, PMCID: PMC10711801, DOI: 10.1109/isbi53787.2023.10230418.
Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction
Lieffrig E, Zeng T, Zhang J, Fontaine K, Fang X, Revilla E, Lu Y, Onofrey J. Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38111738, PMCID: PMC10725741, DOI: 10.1109/isbi53787.2023.10230791.
Generation of Whole-Body FDG Parametric Ki Images From Static PET Images Using Deep Learning
Miao T, Zhou B, Liu J, Guo X, Liu Q, Xie H, Chen X, Chen M, Wu J, Carson R, Liu C. Generation of Whole-Body FDG Parametric Ki Images From Static PET Images Using Deep Learning. IEEE Transactions On Radiation And Plasma Medical Sciences 2023, 7: 465-472. PMID: 37997577, PMCID: PMC10665031, DOI: 10.1109/trpms.2023.3243576.
Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging
Bajaj S, Khunte M, Moily N, Payabvash S, Wintermark M, Gandhi D, Malhotra A. Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging. Journal Of The American College Of Radiology 2023, 20: 1241-1249. PMID: 37574094, DOI: 10.1016/j.jacr.2023.06.034.
Explainable AI for Prostate MRI: Don't Trust, Verify.
Chapiro J. Explainable AI for Prostate MRI: Don't Trust, Verify. Radiology 2023, 307: e230574. PMID: 37039689, PMCID: PMC10323286, DOI: 10.1148/radiol.230574.
2022
Liu X, Marin T, Amal T, Woo J, Fakhri G, Ouyang J. Posterior estimation using deep learning: a simulation study of compartmental modeling in dynamic positron emission tomography. Medical Physics 2022, 50: 1539-1548. PMID: 36331429, PMCID: PMC10087283, DOI: 10.1002/mp.16078.
Multi-tracer Deep Learning for PET Head Motion Correction
Lieffrig E, Zeng T, Zhang J, Fang X, Revilla E, Lu Y, Onofrey J. Multi-tracer Deep Learning for PET Head Motion Correction. 2022, 00: 1-4. DOI: 10.1109/nss/mic44845.2022.10399143.
An Adaptive Patch Sampling Scheme for Deep Learning Based PET Image Denoising
Wu J, Tan H, Liu H, Liu C, Onofrey J. An Adaptive Patch Sampling Scheme for Deep Learning Based PET Image Denoising. 2022, 00: 1-3. DOI: 10.1109/nss/mic44845.2022.10399313.
Flow-Based Visual Quality Enhancer for Super-Resolution Magnetic Resonance Spectroscopic Imaging
Dong S, Hangel G, Chen E, Sun S, Bogner W, Widhalm G, You C, Onofrey J, de Graaf R, Duncan J. Flow-Based Visual Quality Enhancer for Super-Resolution Magnetic Resonance Spectroscopic Imaging. Lecture Notes In Computer Science 2022, 13609: 3-13. DOI: 10.1007/978-3-031-18576-2_1.
Chen X, Zhou B, Xie H, Miao T, Liu H, Holler W, Lin M, Miller EJ, Carson RE, Sinusas AJ, Liu C. DuDoSS: Deep‐learning‐based dual‐domain sinogram synthesis from sparsely sampled projections of cardiac SPECT. Medical Physics 2022, 50: 89-103. PMID: 36048541, PMCID: PMC9868054, DOI: 10.1002/mp.15958.
Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator
Liu X, Xing F, Prince J, Zhuo J, Stone M, El Fakhri G, Woo J. Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator. Lecture Notes In Computer Science 2022, 13436: 376-386. PMID: 36820764, PMCID: PMC9942274, DOI: 10.1007/978-3-031-16446-0_36.
Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives
Liu X, Yoo C, Xing F, Oh H, Fakhri G, Kang J, Woo J. Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives. APSIPA Transactions On Signal And Information Processing 2022, 11: e25. DOI: 10.1561/116.00000192.
MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET
Guo X, Zhou B, Chen X, Liu C, Dvornek N. MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET. Lecture Notes In Computer Science 2022, 13434: 163-172. PMID: 38464686, PMCID: PMC10923180, DOI: 10.1007/978-3-031-16440-8_16.
Supervised Deep Learning for Head Motion Correction in PET
Zeng T, Zhang J, Revilla E, Lieffrig E, Fang X, Lu Y, Onofrey J. Supervised Deep Learning for Head Motion Correction in PET. Lecture Notes In Computer Science 2022, 13434: 194-203. PMID: 38107622, PMCID: PMC10725740, DOI: 10.1007/978-3-031-16440-8_19.
A personalized deep learning denoising strategy for low-count PET images
Liu Q, Liu H, Mirian N, Ren S, Viswanath V, Karp J, Surti S, Liu C. A personalized deep learning denoising strategy for low-count PET images. Physics In Medicine And Biology 2022, 67: 145014. PMID: 35697017, PMCID: PMC9321225, DOI: 10.1088/1361-6560/ac783d.
Virtual high‐count PET image generation using a deep learning method
Liu J, Ren S, Wang R, Mirian N, Tsai Y, Kulon M, Pucar D, Chen M, Liu C. Virtual high‐count PET image generation using a deep learning method. Medical Physics 2022, 49: 5830-5840. PMID: 35880541, PMCID: PMC9474624, DOI: 10.1002/mp.15867.
Deep-Learning-Based Few-Angle Cardiac SPECT Reconstruction Using Transformer
Xie H, Thorn S, Liu Y, Lee S, Liu Z, Wang G, Sinusas A, Liu C. Deep-Learning-Based Few-Angle Cardiac SPECT Reconstruction Using Transformer. IEEE Transactions On Radiation And Plasma Medical Sciences 2022, 7: 33-40. PMID: 37397179, PMCID: PMC10312390, DOI: 10.1109/trpms.2022.3187595.
Guo X, Zhou B, Pigg D, Spottiswoode B, Casey ME, Liu C, Dvornek NC. Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network. Medical Image Analysis 2022, 80: 102524. PMID: 35797734, PMCID: PMC10923189, DOI: 10.1016/j.media.2022.102524.
Deep-learning-based methods of attenuation correction for SPECT and PET
Chen X, Liu C. Deep-learning-based methods of attenuation correction for SPECT and PET. Journal Of Nuclear Cardiology 2022, 30: 1859-1878. PMID: 35680755, DOI: 10.1007/s12350-022-03007-3.
Chen X, Pretorius P, Zhou B, Liu H, Johnson K, Liu YH, King MA, Liu C. Cross-vender, cross-tracer, and cross-protocol deep transfer learning for attenuation map generation of cardiac SPECT. Journal Of Nuclear Cardiology 2022, 29: 3379-3391. PMID: 35474443, PMCID: PMC11407548, DOI: 10.1007/s12350-022-02978-7.
Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction
Xie H, Thorn S, Chen X, Zhou B, Liu H, Liu Z, Lee S, Wang G, Liu YH, Sinusas AJ, Liu C. Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction. Journal Of Nuclear Cardiology 2022, 30: 86-100. PMID: 35508796, DOI: 10.1007/s12350-022-02972-z.
Toyonaga T, Shao D, Shi L, Zhang J, Revilla EM, Menard D, Ankrah J, Hirata K, Chen MK, Onofrey JA, Lu Y. Deep learning–based attenuation correction for whole-body PET — a multi-tracer study with 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 49: 3086-3097. PMID: 35277742, PMCID: PMC10725742, DOI: 10.1007/s00259-022-05748-2.
Joel MZ, Umrao S, Chang E, Choi R, Yang DX, Duncan JS, Omuro A, Herbst R, Krumholz HM, Aneja S. Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology. JCO Clinical Cancer Informatics 2022, 6: e2100170. PMID: 35271304, PMCID: PMC8932490, DOI: 10.1200/cci.21.00170.
Chen X, Liu X, Koundal S, Elkin R, Zhu X, Monte B, Xu F, Dai F, Pedram M, Lee H, Kipnis J, Tannenbaum A, Van Nostrand WE, Benveniste H. Cerebral amyloid angiopathy is associated with glymphatic transport reduction and time-delayed solute drainage along the neck arteries. Nature Aging 2022, 2: 214-223. PMID: 36199752, PMCID: PMC9531841, DOI: 10.1038/s43587-022-00181-4.
VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI
Liu X, Xing F, Yang C, Kuo C, Babu S, Fakhri G, Jenkins T, Woo J. VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI. IEEE Journal Of Biomedical And Health Informatics 2022, 26: 1128-1139. PMID: 34339378, PMCID: PMC8807766, DOI: 10.1109/jbhi.2021.3097735.
Chen X, Zhou B, Xie H, Shi L, Liu H, Holler W, Lin M, Liu YH, Miller EJ, Sinusas AJ, Liu C. Direct and indirect strategies of deep-learning-based attenuation correction for general purpose and dedicated cardiac SPECT. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 49: 3046-3060. PMID: 35169887, PMCID: PMC9253078, DOI: 10.1007/s00259-022-05718-8.
2021
Malpani R, Petty CW, Yang J, Bhatt N, Zeevi T, Chockalingam V, Raju R, Petukhova-Greenstein A, Santana JG, Schlachter TR, Madoff DC, Chapiro J, Duncan J, Lin M. Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach. Journal Of Vascular And Interventional Radiology 2021, 33: 324-332.e2. PMID: 34923098, PMCID: PMC8972393, DOI: 10.1016/j.jvir.2021.12.017.
PET Image Denoising Using a Deep-Learning Method for Extremely Obese Patients
Liu H, Yousefi H, Mirian N, Lin M, Menard D, Gregory M, Aboian M, Boustani A, Chen M, Saperstein L, Pucar D, Kulon M, Liu C. PET Image Denoising Using a Deep-Learning Method for Extremely Obese Patients. IEEE Transactions On Radiation And Plasma Medical Sciences 2021, 6: 766-770. PMID: 37284026, PMCID: PMC10241407, DOI: 10.1109/trpms.2021.3131999.
Gross M, Spektor M, Jaffe A, Kucukkaya AS, Iseke S, Haider SP, Strazzabosco M, Chapiro J, Onofrey JA. Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging. PLOS ONE 2021, 16: e0260630. PMID: 34852007, PMCID: PMC8635384, DOI: 10.1371/journal.pone.0260630.
Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning
Shi L, Lu Y, Dvornek N, Weyman CA, Miller EJ, Sinusas AJ, Liu C. Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning. IEEE Transactions On Medical Imaging 2021, 40: 3293-3304. PMID: 34018932, PMCID: PMC8670362, DOI: 10.1109/tmi.2021.3082578.
Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas
Marin T, Zhuo Y, Lahoud R, Tian F, Ma X, Xing F, Moteabbed M, Liu X, Grogg K, Shusharina N, Woo J, Lim R, Ma C, Chen Y, El Fakhri G. Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas. Radiotherapy And Oncology 2021, 167: 269-276. PMID: 34808228, PMCID: PMC8934266, DOI: 10.1016/j.radonc.2021.09.034.
Super-resolution PET Brain Imaging using Deep Learning
Ren S, Liu J, Xie H, Toyonaga T, Mirian N, Chen M, Aboian M, Carson R, Liu C. Super-resolution PET Brain Imaging using Deep Learning. 2021, 00: 1-6. DOI: 10.1109/nss/mic44867.2021.9875548.
Chen X, Zhou B, Xie H, Shi L, Liu H, Liu C. Investigation of Direct and Indirect Approaches of Deep-Learning-Based Attenuation Correction for General Purpose and Dedicated Cardiac SPECT Scanners. 2021, 00: 1-2. DOI: 10.1109/nss/mic44867.2021.9875517.
Liu H, Wu J, Shi L, Liu Y, Miller E, Sinusas A, Liu YH, Liu C. Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation. Journal Of Nuclear Cardiology 2021, 29: 2881-2892. PMID: 34671940, DOI: 10.1007/s12350-021-02817-1.
Pak D, Liu M, Kim T, Liang L, McKay R, Sun W, Duncan J. Distortion Energy for Deep Learning-Based Volumetric Finite Element Mesh Generation for Aortic Valves. Lecture Notes In Computer Science 2021, 12906: 485-494. DOI: 10.1007/978-3-030-87231-1_47.
Gonzales R, Lamy J, Seemann F, Heiberg E, Onofrey J, Peters D. TVnet: Automated Time-Resolved Tracking of the Tricuspid Valve Plane in MRI Long-Axis Cine Images with a Dual-Stage Deep Learning Pipeline. Lecture Notes In Computer Science 2021, 12906: 567-576. DOI: 10.1007/978-3-030-87231-1_55.
Generative Self-training for Cross-Domain Unsupervised Tagged-to-Cine MRI Synthesis
Liu X, Xing F, Stone M, Zhuo J, Reese T, Prince J, El Fakhri G, Woo J. Generative Self-training for Cross-Domain Unsupervised Tagged-to-Cine MRI Synthesis. Lecture Notes In Computer Science 2021, 12903: 138-148. PMID: 34734217, PMCID: PMC8562649, DOI: 10.1007/978-3-030-87199-4_13.
The promise of awake behaving infant fMRI as a deep measure of cognition
Yates T, Ellis C, Turk-Browne N. The promise of awake behaving infant fMRI as a deep measure of cognition. Current Opinion In Behavioral Sciences 2021, 40: 5-11. DOI: 10.1016/j.cobeha.2020.11.007.
Wang R, Liu H, Toyonaga T, Shi L, Wu J, Onofrey JA, Tsai Y, Naganawa M, Ma T, Liu Y, Chen M, Mecca AP, O’Dell R, van Dyck C, Carson RE, Liu C. Generation of synthetic PET images of synaptic density and amyloid from 18F‐FDG images using deep learning. Medical Physics 2021, 48: 5115-5129. PMID: 34224153, PMCID: PMC8455448, DOI: 10.1002/mp.15073.
Detecting lumbar lesions in 99mTc‐MDP SPECT by deep learning: Comparison with physicians
Petibon Y, Fahey F, Cao X, Levin Z, Sexton‐Stallone B, Falone A, Zukotynski K, Kwatra N, Lim R, Bar‐Sever Z, Chemli Y, Treves S, Fakhri G, Ouyang J. Detecting lumbar lesions in 99mTc‐MDP SPECT by deep learning: Comparison with physicians. Medical Physics 2021, 48: 4249-4261. PMID: 34101855, DOI: 10.1002/mp.15033.
Weakly Supervised Deep Learning for Aortic Valve Finite Element Mesh Generation from 3D CT Images
Pak D, Liu M, Ahn S, Caballero A, Onofrey J, Liang L, Sun W, Duncan J. Weakly Supervised Deep Learning for Aortic Valve Finite Element Mesh Generation from 3D CT Images. Lecture Notes In Computer Science 2021, 12729: 637-648. DOI: 10.1007/978-3-030-78191-0_49.
Nonuniform Fast Fourier Transform on Tpus
Lu T, Marin T, Zhuo Y, Chen Y, Ma C. Nonuniform Fast Fourier Transform on Tpus. 2021, 00: 783-787. DOI: 10.1109/isbi48211.2021.9434068..
Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study
Yang J, Shi L, Wang R, Miller EJ, Sinusas AJ, Liu C, Gullberg GT, Seo Y. Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study. Journal Of Nuclear Medicine 2021, 62: 1645-1652. PMID: 33637586, PMCID: PMC8612332, DOI: 10.2967/jnumed.120.256396.
Diagnostic accuracy of stress-only myocardial perfusion SPECT improved by deep learning
Liu H, Wu J, Miller EJ, Liu C, Yaqiang, Liu, Liu YH. Diagnostic accuracy of stress-only myocardial perfusion SPECT improved by deep learning. European Journal Of Nuclear Medicine And Molecular Imaging 2021, 48: 2793-2800. PMID: 33511425, DOI: 10.1007/s00259-021-05202-9.
Malpani R, Petty C, Bhatt N, Staib L, Chapiro J. Use of Artificial Intelligence in Nononcologic Interventional Radiology: Current State and Future Directions. Digestive Disease Interventions 2021, 05: 331-337. PMID: 35005333, PMCID: PMC8740955, DOI: 10.1055/s-0041-1726300.
2020
Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty
Li X, Zhou Y, Dvornek NC, Gu Y, Ventola P, Duncan JS. Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty. Lecture Notes In Computer Science 2020, 12261: 792-801. PMID: 34308439, PMCID: PMC8299327, DOI: 10.1007/978-3-030-59710-8_77.
Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space
Yang J, Li X, Pak D, Dvornek N, Chapiro J, Lin M, Duncan J. Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space. Lecture Notes In Computer Science 2020, 12444: 52-61. DOI: 10.1007/978-3-030-60548-3_6.
High-performance rapid MR parameter mapping using model-based deep adversarial learning
Liu F, Kijowski R, Feng L, El Fakhri G. High-performance rapid MR parameter mapping using model-based deep adversarial learning. Magnetic Resonance Imaging 2020, 74: 152-160. PMID: 32980503, PMCID: PMC7669737, DOI: 10.1016/j.mri.2020.09.021.
Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET
Liu H, Wu J, Lu W, Onofrey JA, Liu YH, Liu C. Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET. Physics In Medicine And Biology 2020, 65: 185006. PMID: 32924973, PMCID: PMC12434544, DOI: 10.1088/1361-6560/abae08.
Li X, Gu Y, Dvornek N, Staib LH, Ventola P, Duncan JS. Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results. Medical Image Analysis 2020, 65: 101765. PMID: 32679533, PMCID: PMC7569477, DOI: 10.1016/j.media.2020.101765.
Deep learning-based attenuation map generation for myocardial perfusion SPECT
Shi L, Onofrey JA, Liu H, Liu YH, Liu C. Deep learning-based attenuation map generation for myocardial perfusion SPECT. European Journal Of Nuclear Medicine And Molecular Imaging 2020, 47: 2383-2395. PMID: 32219492, DOI: 10.1007/s00259-020-04746-6.
Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation
Onofrey JA, Staib LH, Huang X, Zhang F, Papademetris X, Metaxas D, Rueckert D, Duncan JS. Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation. Annual Review Of Biomedical Engineering 2020, 22: 1-27. PMID: 32169002, PMCID: PMC9351438, DOI: 10.1146/annurev-bioeng-060418-052147.
2019
Deep Learning based Respiratory Pattern Classification and Applications in PET/CT Motion Correction
Guo Y, Dvornek N, Lu Y, Tsai Y, Hamill J, Casey M, Liu C. Deep Learning based Respiratory Pattern Classification and Applications in PET/CT Motion Correction. 2019, 00: 1-5. DOI: 10.1109/nss/mic42101.2019.9059783.
Invertible Network for Classification and Biomarker Selection for ASD
Zhuang J, Dvornek NC, Li X, Ventola P, Duncan JS. Invertible Network for Classification and Biomarker Selection for ASD. Lecture Notes In Computer Science 2019, 11766: 700-708. PMID: 32274471, PMCID: PMC7144624, DOI: 10.1007/978-3-030-32248-9_78.
Yang J, Dvornek NC, Zhang F, Chapiro J, Lin M, Duncan JS. Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation. Lecture Notes In Computer Science 2019, 11765: 255-263. PMID: 32377643, PMCID: PMC7202929, DOI: 10.1007/978-3-030-32245-8_29.
Shi L, Onofrey J, Revilla E, Toyonaga T, Menard D, Ankrah J, Carson R, Liu C, Lu Y. A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation Using Deep Learning. Lecture Notes In Computer Science 2019, 11767: 723-731. DOI: 10.1007/978-3-030-32251-9_79.
Domain-Agnostic Learning with Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation
Yang J, Dvornek NC, Zhang F, Zhuang J, Chapiro J, Lin M, Duncan JS. Domain-Agnostic Learning with Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation. ICCV Workshops 2019, 00: 323-331. PMID: 34676308, PMCID: PMC8528125, DOI: 10.1109/iccvw.2019.00043.
An investigation of quantitative accuracy for deep learning based denoising in oncological PET
Lu W, Onofrey JA, Lu Y, Shi L, Ma T, Liu Y, Liu C. An investigation of quantitative accuracy for deep learning based denoising in oncological PET. Physics In Medicine And Biology 2019, 64: 165019. PMID: 31307019, DOI: 10.1088/1361-6560/ab3242.
Li X, Dvornek NC, Zhou Y, Zhuang J, Ventola P, Duncan JS. Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery. Lecture Notes In Computer Science 2019, 11492: 718-730. PMID: 32982121, PMCID: PMC7519580, DOI: 10.1007/978-3-030-20351-1_56.
Woo J, Xing F, Prince J, Stone M, Green J, Goldsmith T, Reese T, Wedeen V, Fakhri G. Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning. The Journal Of The Acoustical Society Of America 2019, 145: el423-el429. PMID: 31153323, PMCID: PMC6530633, DOI: 10.1121/1.5103191.
Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization
Onofrey JA, Casetti-Dinescu DI, Lauritzen AD, Sarkar S, Venkataraman R, Fan RE, Sonn GA, Sprenkle PC, Staib LH, Papademetris X. Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2019, 00: 348-351. PMID: 32874427, PMCID: PMC7457546, DOI: 10.1109/isbi.2019.8759295.
2018
Sadda P, Imamoglu M, Dombrowski M, Papademetris X, Bahtiyar MO, Onofrey J. Deep-learned placental vessel segmentation for intraoperative video enhancement in fetoscopic surgery. International Journal Of Computer Assisted Radiology And Surgery 2018, 14: 227-235. PMID: 30484115, PMCID: PMC6438174, DOI: 10.1007/s11548-018-1886-4.
Sadda P, Onofrey J, Papademetris X. Deep Learning Retinal Vessel Segmentation from a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks. Lecture Notes In Computer Science 2018, 11043: 82-91. DOI: 10.1007/978-3-030-01364-6_10.
Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets
Dvornek NC, Yang D, Ventola P, Duncan JS. Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets. Lecture Notes In Computer Science 2018, 11072: 329-337. PMID: 30873514, PMCID: PMC6411297, DOI: 10.1007/978-3-030-00931-1_38.
Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI
Li X, Dvornek NC, Zhuang J, Ventola P, Duncan JS. Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI. Lecture Notes In Computer Science 2018, 11072: 206-214. PMID: 32984865, PMCID: PMC7519581, DOI: 10.1007/978-3-030-00931-1_24.
Onofrey JA, Staib LH, Papademetris X. Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning. IEEE Transactions On Medical Imaging 2018, 38: 596-607. PMID: 30176584, PMCID: PMC6476428, DOI: 10.1109/tmi.2018.2868045.
Dvornek NC, Ventola P, Duncan JS. Combining Phenotypic and Resting-State FMRI Data for Autism Classification with Recurrent Neural Networks. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 725-728. PMID: 30288208, PMCID: PMC6166875, DOI: 10.1109/isbi.2018.8363676.
Li X, Dvornek NC, Papademetris X, Zhuang J, Staib LH, Ventola P, Duncan JS. 2-Channel Convolutional 3D Deep Neural Network (2CC3D) for FMRI Analysis: ASD Classification and Feature Learning. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 1252-1255. PMID: 32983370, PMCID: PMC7519578, DOI: 10.1109/isbi.2018.8363798.