Distribution of coronary artery calcium volume and density by age, sex, and race using AI-based quantification algorithm

Gershon G, Zhou K, Yang Y, Yan X, Barr J, Razavi AC, Rapaka S, Dzaye O, Whelton SP, Blaha MJ, et al.

Journal of Cardiovascular Computed Tomography, 2026

Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index

Zsarnoczay E, Varga-Szemes A, Schoepf UJ, Rapaka S, Pinos D, Aquino GJ, Fink N, Vecsey-Nagy M, Tremamunno G, Kravchenko D, et al.

Journal of Cardiovascular Computed Tomography, Vol. 19(2):201–207, 2025

Artificial intelligence improves prediction of major adverse cardiovascular events in patients undergoing transcatheter aortic valve replacement planning CT

Tremamunno G, Vecsey-Nagy M, Schoepf UJ, Zsarnoczay E, Aquino GJ, Kravchenko D, Jacob A, Sharma P, Rapaka S, et al.

Academic Radiology, Vol. 32(2):702–711, 2025

Accuracy of a deep neural network for automated pulmonary embolism detection on dedicated CT pulmonary angiograms

Zsarnoczay E, Rapaka S, Schoepf UJ, Gnasso C, Vecsey-Nagy M, Todoran TM, Hagar MT, Kravchenko D, Tremamunno G, et al.

European Journal of Radiology, Vol. 187:112077, 2025

The evolution of computer-assisted detection of pulmonary embolism from volume to voxel

Condrea F, Rapaka S, Itu LM, Leordeanu M

Journal of Cardiovascular Emergencies, Vol. 11(1):1–10, 2025

Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study

Rajagopal JR, Rapaka S, Farhadi F, Abadi E, Segars WP, Nowak T, Sharma P, Pritchard WF, Malayeri A, Jones EC, et al.

Scientific Reports, Vol. 15(1):28814, 2025

Artificial intelligence-based bi-ventricular systolic and diastolic volume, ejection fraction using non-contrast ECG-gated cardiac computed tomography

Chao MF, Jacob AJ, Sinha A, Hallam K, Kragholm KH, Sharma P, Rapaka S, Ramirez-Giraldo JC, Chang SM

European Heart Journal – Imaging Methods and Practice, Vol. 3(4):qyaf121, 2025

AI-derived cohort analysis of sex and race differences in CAC volume and density

Gershon G, Razavi AC, Dzaye O, Whelton SP, Blaha MJ, Blumenthal RS, Sperling LS, Rapaka S, De Cecco CN, Van Assen M

Journal of the American College of Cardiology, Vol. 85(12 Suppl):2084, 2025 · ACC Meeting Abstract

AI-based cardiac chamber volumetry from CAC CT enhances heart failure prediction beyond PREVENT-HF

Barr J, Gershon G, Momin E, Rapaka S, Jacob A, Rim A, Zhou B, De Cecco C, Van Assen M

Circulation, Vol. 152(Suppl 3):A4366874, 2025 · AHA Meeting Abstract

Phase matters: diastolic versus systolic chamber volumetry from CAC CT scans in heart failure risk stratification

Barr J, Gershon G, Momin E, Rapaka S, Jacob A, Rim A, De Cecco C, Van Assen M

Circulation, Vol. 152(Suppl 3):A4366856, 2025 · AHA Meeting Abstract

Explainable machine learning for risk stratification of major adverse cardiac events using clinical and imaging data

Gershon G, Yan X, Adibi A, Gabriel R, Kittisut N, Rapaka S, De Cecco C, Van Assen M

Circulation, Vol. 152(Suppl 3):A4366633, 2025 · AHA Meeting Abstract

Anatomically aware dual-hop learning for pulmonary embolism detection in CT pulmonary angiograms

Condrea F, Rapaka S, Itu LM, Sharma P, Sperl J, Ali AM, Leordeanu M

Computers in Biology and Medicine, Vol. 174:108464, 2024

Artificial intelligence provides accurate quantification of thoracic aortic enlargement and dissection in chest CT

Fink N, Yacoub B, Schoepf UJ, Zsarnoczay E, Pinos D, Vecsey-Nagy M, Rapaka S, Sharma P, O'Doherty J, Ricke J, et al.

Diagnostics, Vol. 14(9):866, 2024

Fully automated assessment of cardiac chamber volumes and myocardial mass on non-contrast chest CT with a deep learning model: validation against cardiac MR

Schmitt R, Schlett CL, Sperl JI, Rapaka S, Jacob AJ, Hein M, Hagar MT, Ruile P, Westermann D, Soschynski M, et al.

Diagnostics, Vol. 14(24):2884, 2024

Label up: learning pulmonary embolism segmentation from image-level annotation through model explainability

Condrea F, Rapaka S, Leordeanu M

arXiv preprint, arXiv:2412.07384, 2024

Iterative explainability for weakly supervised segmentation in medical PE detection

Condrea F, Rapaka S, Leordeanu M

arXiv preprint, arXiv:2412.07384, 2024

AI-based, automated chamber volumetry from gated, non-contrast CT

Jacob AJ, Abdelkarim O, Zook S, Kragholm KH, Gupta P, Cocker M, Giraldo JR, Doherty JO, Schoebinger M, Schwemmer C, Rapaka S, Sharma P, et al.

Journal of Cardiovascular Computed Tomography, Vol. 17(5):336–340, 2023

Validation of a convolutional neural network algorithm for calcium score quantification using a multivendor dataset

Muscogiuri E, van Assen M, Tessarin G, Razavi A, Schwemmer C, Schoebinger M, Wels M, Rapaka S, Fung GSK, Stillman A, et al.

Journal of Cardiovascular Computed Tomography, Vol. 17(6):473, 2023

Impact of retraining a deep learning algorithm for improving guideline-compliant aortic diameter measurements on non-gated chest CT

Piccolo FL, Hinck D, Segeroth M, Sperl J, Cyriac J, Yang S, Rapaka S, Bremerich J, Sauter AW, Pradella M

European Journal of Radiology, Vol. 168:111093, 2023

Deep learning for vessel-specific coronary artery calcium scoring: validation on a multi-centre dataset

Winkel DJ, Suryanarayana VR, Ali AM, Görich J, Buß SJ, Mendoza A, Schwemmer C, Sharma P, Schoepf UJ, Rapaka S

European Heart Journal – Cardiovascular Imaging, Vol. 23(6):846–854, 2022

Performance of an artificial intelligence-based platform against clinical radiology reports for the evaluation of noncontrast chest CT

Yacoub B, Kabakus IM, Schoepf UJ, Giovagnoli VM, Fischer AM, Wichmann JL, Martinez JD, Sharma P, Rapaka S, Sahbaee P, et al.

Academic Radiology, Vol. 29:S108–S117, 2022

Personalized pre- and post-operative hemodynamic assessment of aortic coarctation from 3D rotational angiography

Nita CI, Puiu A, Bunescu D, Itu LM, Mihalef V, Chintalapani G, Armstrong A, Zampi J, Benson L, Sharma P, Rapaka S

Cardiovascular Engineering and Technology, Vol. 13(1):14–40, 2022

Performance of a deep learning tool to detect missed aortic dilatation in a large chest CT cohort

Pradella M, Achermann R, Sperl JI, Kargel R, Rapaka S, Cyriac J, Yang S, Sommer G, Stieltjes B, Bremerich J, et al.

Frontiers in Cardiovascular Medicine, Vol. 9:972512, 2022

Normalizing flows for out-of-distribution detection: application to coronary artery segmentation

Ciudel CF, Itu LM, Cimen S, Wels M, Schwemmer C, Fortner P, Seitz S, Andre F, Buss SJ, Sharma P, Rapaka S

Applied Sciences, Vol. 12(8):3839, 2022

Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value

Chamberlin J, Kocher MR, Waltz J, Snoddy M, Stringer NFC, Stephenson J, Sahbaee P, Sharma P, Rapaka S, Schoepf UJ, et al.

BMC Medicine, Vol. 19(1):55, 2021

Automatic coronary calcium scoring in chest CT using a deep neural network in direct comparison with non-contrast cardiac CT: a validation study

van Assen M, Martin SS, Varga-Szemes A, Rapaka S, Cimen S, Sharma P, Sahbaee P, De Cecco CN, Vliegenthart R, Leonard TJ, et al.

European Journal of Radiology, Vol. 134:109428, 2021

Prediction of patient management in COVID-19 using deep learning-based fully automated extraction of cardiothoracic CT metrics and laboratory findings

Weikert T, Rapaka S, Grbic S, Re T, Chaganti S, Winkel DJ, Anastasopoulos C, Niemann T, Wiggli BJ, Bremerich J, et al.

Korean Journal of Radiology, Vol. 22(6):994, 2021

Evaluation of a deep learning–based automated CT coronary artery calcium scoring algorithm

Martin SS, van Assen M, Rapaka S, Hudson HT Jr, Fischer AM, Varga-Szemes A, Sahbaee P, Schwemmer C, Gulsun MA, Cimen S, et al.

JACC: Cardiovascular Imaging, Vol. 13(2):524–526, 2020

Rupture risk of small unruptured intracranial aneurysms in Japanese adults

Suzuki T, Takao H, Rapaka S, Fujimura S, Nita CI, Uchiyama Y, Ohno H, Otani K, Dahmani C, Mihalef V, et al.

Stroke, Vol. 51(2):641–643, 2020

An automated workflow for hemodynamic computations in cerebral aneurysms

Nita CI, Suzuki T, Itu LM, Mihalef V, Takao H, Murayama Y, Sharma P, Redel T, Rapaka S

Computational and Mathematical Methods in Medicine, Vol. 2020:5954617, 2020

Machine learning and coronary artery calcium scoring

Lee H, Martin S, Burt JR, Bagherzadeh PS, Rapaka S, Gray HN, Leonard TJ, Schwemmer C, Schoepf UJ

Current Cardiology Reports, Vol. 22(9):90, 2020

Implementation of a patient-specific cardiac model

Mihalef V, Mansi T, Rapaka S, Passerini T

Artificial Intelligence for Computational Modeling of the Heart, pp. 43–94, Academic Press, 2020 · Book Chapter

Additional clinical applications

Meister F, Houle H, Nita C, Puiu A, Itu LM, Rapaka S

Artificial Intelligence for Computational Modeling of the Heart, pp. 183–210, Academic Press, 2020 · Book Chapter

Coronary CT angiography–derived fractional flow reserve: machine learning algorithm versus computational fluid dynamics modeling

Tesche C, De Cecco CN, Baumann S, Renker M, McLaurin TW, Duguay TM, Bayer RR, Steinberg DH, Grant KL, Canstein C, Rapaka S (co-author), et al.

Radiology, Vol. 288(1):64–72, 2018

Diagnostic accuracy of a machine-learning approach to coronary computed tomographic angiography–based fractional flow reserve: result from the MACHINE consortium

Coenen A, Kim YH, Kruk M, Tesche C, De Geer J, Kurata A, Lubbers ML, Daemen J, Itu L, Rapaka S, et al.

Circulation: Cardiovascular Imaging, Vol. 11(6):e007217, 2018

Real-world variability in the prediction of intracranial aneurysm wall shear stress: the 2015 international aneurysm CFD challenge

Valen-Sendstad K, Bergersen AW, Shimogonya Y, Goubergrits L, Bruening J, Pallares J, ..., Rapaka S (co-author), et al.

Cardiovascular Engineering and Technology, Vol. 9(4):544, 2018

Comprehensive preclinical evaluation of a multi-physics model of liver tumor radiofrequency ablation

Audigier C, Mansi T, Delingette H, Rapaka S, Passerini T, Mihalef V, Jolly MP, Pop R, Diana M, Soler L, et al.

International Journal of Computer Assisted Radiology and Surgery, Vol. 12(9):1543–1559, 2017

A machine-learning approach for computation of fractional flow reserve from coronary computed tomography

Itu L, Rapaka S, Passerini T, Georgescu B, Schwemmer C, Schoebinger M, Flohr T, Sharma P, Comaniciu D

Journal of Applied Physiology, Vol. 121(1):42–52, 2016

Coronary centerline extraction via optimal flow paths and CNN path pruning

Gülsün MA, Funka-Lea G, Sharma P, Rapaka S, Zheng Y

MICCAI 2016, pp. 317–325 · Conference Paper

Verification of a research prototype for hemodynamic analysis of cerebral aneurysms

Suzuki T, Nita CI, Rapaka S, Takao H, Mihalef V, Fujimura S, Dahmani C, Sharma P, Mamori H, Ishibashi T, et al.

IEEE EMBC 2016, pp. 2921–2924 · Conference Paper

GPU accelerated, robust method for voxelization of solid objects

Nita C, Stroia I, Itu L, Suciu C, Mihalef V, Datar M, Rapaka S, Sharma P

IEEE HPEC 2016, pp. 1–5 · Conference Paper

Challenges to validate multi-physics model of liver tumor radiofrequency ablation from pre-clinical data

Audigier C, Mansi T, Delingette H, Rapaka S, Passerini T, Mihalef V, Pop R, Diana M, Soler L, Kamen A, et al.

Computational Biomechanics for Medicine, pp. 27–38, Springer, 2016 · Book Chapter

Efficient lattice Boltzmann solver for patient-specific radiofrequency ablation of hepatic tumors

Audigier C, Mansi T, Delingette H, Rapaka S, Mihalef V, Carnegie D, Boctor E, Choti M, Kamen A, Ayache N, et al.

IEEE Transactions on Medical Imaging, Vol. 34(7):1576–1589, 2015

GPU-accelerated model for fast, three-dimensional fluid-structure interaction computations

Nita C, Itu L, Mihalef V, Sharma P, Rapaka S

IEEE EMBC 2015, pp. 965–968 · Conference Paper

Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals

Zettinig O, Mansi T, Neumann D, Georgescu B, Rapaka S, Seegerer P, Kayvanpour E, Sedaghat-Hamedani F, Amr A, Haas J, et al.

Medical Image Analysis, Vol. 18(8):1361–1376, 2014

A simulator for modeling coupled thermo-hydro-mechanical processes in subsurface geological media

Kelkar S, Lewis K, Karra S, Zyvoloski G, Rapaka S, Viswanathan H, Mishra PK, Chu S, Coblentz D, Pawar R

International Journal of Rock Mechanics and Mining Sciences, Vol. 70:569–580, 2014

Parameter estimation for personalization of liver tumor radiofrequency ablation

Audigier C, Mansi T, Delingette H, Rapaka S, Mihalef V, Carnegie D, Boctor E, Choti M, Kamen A, Comaniciu D, et al.

MICCAI Workshop on Abdominal Imaging, pp. 3–12, 2014 · Conference Paper

Lattice Boltzmann method for fast patient-specific simulation of liver tumor ablation from CT images

Audigier C, Mansi T, Delingette H, Rapaka S, Mihalef V, Sharma P, Carnegie D, Boctor E, Choti M, Kamen A, et al.

MICCAI 2013, pp. 323–330 · Conference Paper

From medical images to fast computational models of heart electromechanics: an integrated framework towards clinical use

Zettinig O, Mansi T, Georgescu B, Rapaka S, Kamen A, Haas J, Frese KS, Sedaghat-Hamedani F, Kayvanpour E, Amr A, et al.

FIMH 2013, pp. 249–258 · Conference Paper

Model-based estimation of 4D relative pressure map from 4D flow MR images

Mihalef V, Rapaka S, Gulsun MA, Scorza A, Sharma P, Itu L, Kamen A, Barker A, Markl M, Comaniciu D

STACOM 2013, pp. 236–243 · Conference Paper

A framework for the pre-clinical validation of LBM-EP for the planning and guidance of ventricular tachycardia ablation

Mansi T, Beinart R, Zettinig O, Rapaka S, Georgescu B, Kamen A, Dori Y, Zviman MM, Herzka DA, Halperin HR, et al.

STACOM 2013, pp. 253–261 · Conference Paper

LBM-EP: Lattice-Boltzmann method for fast cardiac electrophysiology simulation from 3D images

Rapaka S, Mansi T, Georgescu B, Pop M, Wright GA, Kamen A, Comaniciu D

MICCAI 2012, pp. 33–40 · Conference Paper

Data-driven computational models of heart anatomy, mechanics and hemodynamics: an integrated framework

Mansi T, Mihalef V, Sharma P, Georgescu B, Zheng X, Rapaka S, Kamen A, Mereles D, Steen H, Meder B, et al.

IEEE ISBI 2012, p. 1434 · Conference Paper

Coupled plastic failure and permeability in rocks: a modeling approach

Kelkar S, Karra S, Zyvoloski G, Pawar R, Rapaka S

ARMA Rock Mechanics/Geomechanics Symposium 2012 · Conference Paper

Impact of background flow on dissolution trapping of carbon dioxide injected into saline aquifers

Rapaka S, Pawar RJ

arXiv preprint, arXiv:1101.2677, 2011

Onset of convection over a transient base-state in anisotropic and layered porous media

Rapaka S, Pawar RJ, Stauffer PH, Zhang D, Chen S

Journal of Fluid Mechanics, Vol. 641:227–244, 2009

Flow patterns in the sedimentation of an elliptical particle

Xia Z, Connington KW, Rapaka S, Yue P, Feng JJ, Chen S

Journal of Fluid Mechanics, Vol. 625:249–272, 2009

Non-modal growth of perturbations in density-driven convection in porous media

Rapaka S, Chen S, Pawar RJ, Stauffer PH, Zhang D

Journal of Fluid Mechanics, Vol. 609:285–303, 2008