Milan Sonka, PhD

Portrait
Associate Dean, College of Engineering
Co-director, Iowa Institute for Biomedical Imaging
Professor of Electrical and Computer Engineering (ECE)
Professor of Radiation Oncology
Professor of Ophthalmology and Visual Sciences
Professor of Biomedical Engineering (BME)

Contact Information

Iowa City, IA 52242
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Office: 4013 Seamans Center
Iowa City, IA 52242
319-335-6052

Primary Office: 3016B SC
319-335-5191

Education

Center, Program and Institute Affiliations

Aging Mind and Brain Initiative, Iowa Institute for Biomedical Imaging

Publications

Zhang, L., Wahle, A., Chen, Z., Lopez, J. J., Kovarnik, T. & Sonka, M. (2018). Predicting Locations of High-Risk Plaques in Coronary Arteries in Patients Receiving Statin Therapy. IEEE transactions on medical imaging, 37(1), 151--161.

Guo, Z., Zhang, L., Lu, L., Bagheri, M., Summers, R. M., Sonka, M. & Yao, J. (2018). Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans. arXiv preprint arXiv:1801.08599.

Miri, M. S., Abramoff, Michael D,, Kwon, Y. H., Sonka, M. & Garvin, M. K. (2017). A machine-learning graph-based approach for 3D segmentation of Bruch?s membrane opening from glaucomatous SD-OCT volumes. Medical image analysis, 39, 206--217.

Isack, H., Veksler, O., Oguz, I., Sonka, M. & Boykov, Y. (2017). Efficient optimization for hierarchically-structured interacting segments (HINTS). In Proc. of CVPR.

Kim, Y., Patwardhan, K. A., Beichel, R. R., Smith, B. J., Mart, C., Plichta, K. A., Chang, T., Sonka, M., Graham, M. M., Magnotta, V. & others, (2017). Development of a radiobiological evaluation tool to assess the expected clinical impacts of contouring accuracy between manual and semi-automated segmentation algorithms. In Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE. pp. 3409--3412.

Kashyap, S., Zhang, H. & Sonka, M. (2017). Accurate Fully Automated 4D Segmentation of Osteoarthritic Knee MRI. (Vols. 25). pp. S227--S228. Osteoarthritis and Cartilage.

Kashyap, S., Wahle, A., Zhang, H. & Sonka, M. (2017). Automated Prediction of Cartilage Thickness Changes in OAI MR Dataset. (Vols. 25). pp. S225--S226. Osteoarthritis and Cartilage.

Zhang, L., Sonka, M., Lu, L., Summers, R. M. & Yao, J. (2017). Combining fully convolutional networks and graph-based approach for automated segmentation of cervical cell nuclei. In Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on. pp. 406--409.

Kovarnik, T., Chen, Z., Wahle, A., Zhang, L., Skalicka, H., Krala, A., Lopez, J. J., Horak, J., Sonka, M. & Linhart, A. (2017). Fenotipo del engrosamiento intimal patologico: no tan inocente como se pensaba. Estudio de la histologia virtual de una serie de casos con ecografia intravascular 3D. Revista Espanola de Cardiologia, 70(1), 25--33.

Chen, Z., Wahle, A., Guo, Z., Zhang, H., Karmazin, V., Tomasek, A., Bedanova, H., Lopez, J., Kovarnik, T., Pazdernik, M. & others, (2017). Highly Automated Analysis of Intimal and Medial Thickness in Heart-Transplant Coronary OCT Facilitates Longitudinal Studies of CAV Progression. (Vols. 36). (4), pp. S155. The Journal of Heart and Lung Transplantation.

Lee, K., Zhang, H., Wahle, A., Abràmoff, M. D. & Sonka, M. (2017). Multi-layer 3D Simultaneous Retinal OCT Layer Segmentation: Just-Enough Interaction for Routine Clinical Use. In European Congress on Computational Methods in Applied Sciences and Engineering. pp. 862–871. VipImage.

Kovarnik, T., Chen, Z., Mintz, G. S., Wahle, A., Bayerova, K., Kral, A., Chval, M., Kopriva, K., Lopez, J., Sonka, M. & others, (2017). Plaque volume and plaque risk profile in diabetic vs. non-diabetic patients undergoing lipid-lowering therapy: a study based on 3D intravascular ultrasound and virtual histology. (Vols. 16). (1), pp. 156. Cardiovascular diabetology.

Kashyap, S., Zhang, H., Rao, K. & Sonka, M. (2017). Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative. IEEE Transactions on Medical Imaging.

Lee, K., Han, I. C., Critser, D. B., Wahle, A., Sonka, M. & Abramoff, M. D. (2017). Layer-Specific Vascular Analysis of OCT Angiography in Diabetic Macular Edema. (Vols. 58). (8), pp. 644--644. Investigative Ophthalmology \& Visual Science.

Pazdernik, M., Kovarnik, T., Chen, Z., Wahle, A., Karmazin, V., Melenovsky, V., Kautzner, J., Tomasek, A., Bedanova, H. & Sonka, M. (2017). Increased Heart Rate After Heart Transplant Is Not Associated with Early Progression of Cardiac Allograft Vasculopathy (CAV)-A Prospective Study Using Highly Automatic Coronary Optical Coherence Tomography Segmentation Software in 3D. (Vols. 36). (4), pp. S297--S298. The Journal of Heart and Lung Transplantation.

Pazdernik, M., Bedanova, H., Kautzner, J., Melenovsky, V., Karmazin, V., Tomasek, A., Kovarnik, T., Malek, I., Wahle, A., Chen, Z. & others, (2017). Insights to pathophysiology and risk factors of cardiac allograft vasculopathy: A prospective study using highly automated coronary optical coherence tomography segmentation software in 3D. (Vols. 38). (suppl_1) European Heart Journal.

Kashyap, S., Zhang, H. & Sonka, M. (2017). Just Enough Interaction for Fast Minimally Interactive Correction of 4D Segmentation of Knee MRI. (Vols. 25). pp. S224--S225. Osteoarthritis and Cartilage.

Pazdernik, M., Kovarnik, T., Sonka, M., Wahle, A., Chen, Z., Karmazin, V., Kautzner, J., Tomasek, A., Melenovsky, V. & Bedanova, H. (2017). Should We Pharmacologically Modulate Renin-Aldosterone-Angiotensin System (RAAS) to Attenuate Cardiac Allograft Vasculopathy? A Prospective Study Using Highly Automated Coronary Optical Coherence Tomography Segmentation Software in 3D. (Vols. 36). (4), pp. S292. The Journal of Heart and Lung Transplantation.

Klimscha, S., Waldstein, S. M., Schlegl, T., Bogunovic, H., Sadeghipour, A., Philip, A. M., Podkowinski, D., Pablik, E., Zhang, L., Abramoff, M. D., Sonka, M., Gerendas, B. S. & Schmidt-Erfurth, U. (2017). Spatial Correspondence Between Intraretinal Fluid, Subretinal Fluid, and Pigment Epithelial Detachment in Neovascular Age-Related Macular Degeneration. Investigative ophthalmology & visual science, 58(10), 4039-4048. PMID: 28813577.

Xiang, D., Bagci, U., Jin, C., Shi, F., Zhu, W., Yao, J., Sonka, M. & Chen, X. (2017). CorteXpert: A model-based method for automatic renal cortex segmentation. Medical image analysis, 42, 257-273. PMID: 28888170.

Kovarnik, T., Chen, Z., Wahle, A., Zhang, L., Skalicka, H., Kral, A., Lopez, J. J., Horak, J., Sonka, M. & Linhart, A. (2017). Pathologic Intimal Thickening Plaque Phenotype: Not as Innocent as Previously Thought. A Serial 3D Intravascular Ultrasound Virtual Histology Study. Revista espanola de cardiologia (English ed.), 70(1), 25-33. PMID: 27615562.

Guo, Z., Kwon, Y. H., Lee, K., Wang, K., Wahle, A., Alward WLM,, Fingert, J. H., Bettis, D. I., Johnson, C. A., Garvin, M. K., Sonka, M. & Abràmoff, M. D. (2017). Optical Coherence Tomography Analysis Based Prediction of Humphrey 24-2 Visual Field Thresholds in Patients With Glaucoma. Investigative ophthalmology & visual science, 58(10), 3975-3985. PMID: 28796875.

Miri, M. S., Abràmoff, M. D., Kwon, Y. H., Sonka, M. & Garvin, M. K. (2017). A machine-learning graph-based approach for 3D segmentation of Bruch's membrane opening from glaucomatous SD-OCT volumes. Medical image analysis, 39, 206-217. PMID: 28528295.

Guo, Z., Kashyap, S., Sonka, M. & Oguz, I. (2017). Machine learning in a graph framework for subcortical segmentation. (Vols. 10133). Proceedings of SPIE. PMID: 28626291.

Zhang, L., Kong, H., Liu, S., Wang, T., Chen, S. & Sonka, M. (2017). Graph-based segmentation of abnormal nuclei in cervical cytology. Computerized medical imaging and graphics: the official journal of the Computerized Medical Imaging Society, 56, 38-48. PMID: 28222324.

Klein, B. E., Johnson, C. A., Meuer, S. M., Lee, K., Wahle, A., Lee, K. E., Kulkarni, A., Sonka, M., Abràmoff, M. D. & Klein, R. (2017). Nerve Fiber Layer Thickness and Characteristics Associated with Glaucoma in Community Living Older Adults: Prelude to a Screening Trial?. Ophthalmic epidemiology, 24(2), 104-110. PMID: 28032805.

Choi, C. S., Zhang, L., Abramoff, M. D., Sonka, M., Shifera, A. S. & Kay, C. N. (2016). Evaluating Efficacy of Aflibercept in Refractory Exudative Age-Related Macular Degeneration With OCT Segmentation Volumetric Analysis. Ophthalmic Surgery Lasers Imaging Retina, 47(3), 245-51. PMID: 26985798.

Vimr, R., Kovarnik, T., Chen, Z., Downe, R., Wahle, A., Sonka, M. & Lopez, J. (2016). Geographic Analysis of Coronary Atherosclerosis in a Serial Intravascular Ultrasound Radiofrequency Study: Is the Hot Spot Hypothesis Related to Phenotypic Differences or a Function of Plaque Burden?. (Vols. 87). pp. S72. Catheterization and Cardiovascular Interventions.

Chen, Z., Wahle, A., Zhang, L., Kovarnik, T., Lopez, J. J. & Sonka, M. (2016). Comprehensive serial study of dynamic remodeling of atherosclerotic coronary arteries using IVUS. In Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. (Vols. 9788). pp. 97880Y.

Chen, Z., Wahle, A., Skalicka, H., Kral, A., Lopez, J., Kovarnik, T. & Sonka, M. (2016). EFFECT OF UPSTREAM AND DOWNSTREAM BIFURCATION PROXIMITY ON CORONARY PLAQUE CHANGES AFTER 1 YEAR USING COMPUTER AIDED INTRAVASCULAR ULTRASOUND ANALYSIS. (Vols. 13). (67), pp. 273. Journal of the American College of Cardiology.

Miri, M. S., Ghayoor, A., Johnson, H. J. & Sonka, M. (2016). Comparative study of multimodal intra-subject image registration methods on a publicly available database. In Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. (Vols. 9788). pp. 97881Z.

Isack, H., Veksler, O., Sonka, M. & Boykov, Y. (2016). Hedgehog shape priors for multi-object segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 2434--2442.

Kral, A,, Kovarnik, T., Vanickova, Z,, Skalicka, H,, Horak, J,, Bayerova, K,, Chen, Z., Wahle, A., Zhang, L., Kopriva, K, & others, (2016). Cystatin C Is Associated with the Extent and Characteristics of Coronary Atherosclerosis in Patients with Preserved Renal Function. Folia Biologica (Praha), 62, 225--234.

Kovarnik, T., Jerabek, S., Chen, Z., Wahle, A., Zhang, L., Dostalova, G., Skalicka, H., Kral, A., Horak, J., Sonka, M. & others, (2016). Non-invasive endothelial function assessment using digital reactive hyperaemia correlates with three-dimensional intravascular ultrasound and virtual histology-derived plaque volume and plaque phenotype. Kardiologia polska, 74(12), 1485.

Kovarnik, T., Chen, Z., Wahle, A., Skalicka, H., Kral, A., Lee, K., Zhang, L., Meliska, M., Lopez, J., Sonka, M. & others, (2016). IS RETINAL LAYER THICKNESS RELATED TO CORONARY ATHEROSCLEROSIS? A STUDY WITH RETINAL OPTICAL COHERENCE TOMOGRAPHY AND CORONARY INTRAVASCULAR ULTRASOUND-VH. (Vols. 13). (67), pp. 359. Journal of the American College of Cardiology.

Rashid, A., Waldstein, S. M., Gerendas, B. S., Bogunovic, H., Wahle, A., Lee, K., Wang, K., Simader, C., Abramoff, M. D., Schmidt-Erfurth, U. & others, (2016). Reproducibility of Retinal Thickness Measurements across Spectral-Domain Optical Coherence Tomography Devices using Iowa Reference Algorithm. arXiv preprint arXiv:1612.06442.

Kashyap, S., Oguz, I. & Sonka, M. (2016). Statistical shape analysis of automatically segmented femur bones: Data from the osteoarthritis initiative. In Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on. pp. 651--655.

Kovarnik, T., Chen, Z., Wahle, A., Kral, A., Chval, M., Kopriva, K., Lopez, J., Sonka, M., Linhart, A. & others, (2016). Progression of coronary atherosclerosis despite lipid-lowering therapy in diabetic patients compared to non-dibetic ones. Study with 3D intravascular ultrasound and virtual histology. (Vols. 18). (68), pp. B39. Journal of the American College of Cardiology.

Oguz, I., Zhang, L., Abramoff, Michael D, & Sonka, M. (2016). Optimal retinal cyst segmentation from OCT images. In Medical Imaging 2016: Image Processing. (Vols. 9784). pp. 97841E.

Zhang, L., Wahle, A., Chen, Z., Lopez, J., Kovarnik, T. & Sonka, M. (2016). Location-specific prediction of vulnerable plaque using IVUS, virtual histology, and spatial context. In Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on. pp. 1354--1358.

Oguz, I., Bogunovic, H,, Kashyap, S., Abramoff, MD,, Wu, X. & Sonka, M. (2016). LOGISMOS: A Family of Graph-Based Optimal Image Segmentation Methods. In Medical Image Recognition, Segmentation and Parsing. pp. 179--208.

Lee, K., Buitendijk, G. H., Bogunovic, H., Springelkamp, H., Hofman, A., Wahle, A., Sonka, M., Vingerling, J. R., Klaver, C. C. & Abramoff, M. D. (2016). Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images. (Vols. 5). (2), pp. 14. Translational Vision Science & Technology. PMID: 27066311.

Oguz, I., Kashyap, S., Wang, H., Yushkevich, P. & Sonka, M. (2016). Globally Optimal Label Fusion with Shape Priors. (Vols. 9901). pp. 538-546. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. PMID: 28626843.

Kashyap, S., Oguz, I., Zhang, H. & Sonka, M. (2016). Automated Segmentation of Knee MRI Using Hierarchical Classifiers and Just Enough Interaction Based Learning: Data from Osteoarthritis Initiative. (Vols. 9901). pp. 344-351. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. PMID: 28626842.

Sohn, E. H., van Dijk, H. W., Jiao, C., Kok, P. H., Jeong, W., Demirkaya, N., Garmager, A., Wit, F., Kucukevcilioglu, M., van Velthoven, M. E., DeVries, J. H., Mullins, R. F., Kuehn, M. H., Schlingemann, R. O., Sonka, M., Verbraak, F. D. & Abramoff, M. D. (2016). Retinal neurodegeneration may precede microvascular changes characteristic of diabetic retinopathy in diabetes mellitus. Proceedings of the National Academy of Sciences USA, 113(19), E2655-E64. PMID: 27114552.

Philip, A. M., Gerendas, B. S., Zhang, L., Faatz, H., Podkowinski, D., Bogunovic, H., Abramoff, M. D., Hagmann, M., Leitner, R., Simader, C., Sonka, M., Waldstein, S. M. & Schmidt-Erfurth, U. (2016). Choroidal thickness maps from spectral domain and swept source optical coherence tomography: algorithmic versus ground truth annotation. British journal of ophthalmology, 100(10), 1372-1376. PMID: 26769670.

Sonka, M., Abràmoff, M. D. (2016). Quantitative analysis of retinal OCT. Medical image analysis, 33, 165-169. PMID: 27503080.

Oguz, I., Abramoff, M. D., Zhang, L., Lee, K., Zhang, E. Z. & Sonka, M. (2016). 4D Graph-Based Segmentation for Reproducible and Sensitive Choroid Quantification From Longitudinal OCT Scans. Investigative ophthalmology & visual science, 57(9), OCT621-OCT630. PMID: 27936264.

Beichel, R. R., Van Tol, M., Ulrich, E. J., Bauer, C., Chang, T., Plichta, K. A., Smith, B. J., Sunderland, J. J., Graham, M. M., Sonka, M. & Buatti, J. M. (2016). Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach. Medical physics, 43(6), 2948-2964. PMID: 27277044.

Hirai, T., Chen, Z., Zhang, L., Baaj, S., Kovarnik, T., Porcaro, K., Kaminski, J., Hawn, S., Agrawal, A., Makki, N., Downe, R., Wahle, A., Sonka, M. & Lopez, J. J. (2016). Evaluation of Variable Thin-Cap Fibroatheroma Definitions and Association of Virtual Histology-Intravascular Ultrasound Findings With Cavity Rupture Size. American journal of cardiology, 118(2), 162-169. PMID: 27289292.

Zhang, L., Liu, S., Wang, T., Chen, S. & Sonka, M. (2015). Improved segmentation of abnormal cervical nuclei using a graph-search based approach. In Medical Imaging 2015: Digital Pathology. (Vols. 9420). pp. 94200W.

Bogunovic, Hrvoje,, Abramoff, Michael D, & Sonka, M. (2015). Geodesic graph cut based retinal fluid segmentation in optical coherence tomography. University of Iowa.

Zhang, L., Wahle, A., Chen, Z., Downe, R., Lopez, J., Kovarnik, T. & Sonka, M. (2015). An integrated framework for spatio-temporal registration of intravascular ultrasound pullbacks. In Medical Imaging 2015: Ultrasonic Imaging and Tomography. (Vols. 9419). pp. 94190Y.

Lee, K., Zhang, L., Abramoff, M. D. & Sonka, M. (2015). Fast and memory-efficient LOGISMOS graph search for intraretinal layer segmentation of 3D macular OCT scans. In Medical Imaging 2015: Image Processing. (Vols. 9413). pp. 94133X.

Zhang, L., Wahle, A., Chen, Z., Zhang, L., Downe, R., Kovarnik, T. & Sonka, M. (2015). Joint registration of location and orientation of intravascular ultrasound pullbacks using a 3D graph based method. In Medical Imaging 2015: Image Processing. (Vols. 9413). pp. 94131I.

Shi, F., Chen, X., Zhao, H., Zhu, W., Xiang, D., Gao, E., Sonka, M. & Chen, H. (2015). Automated 3-D retinal layer segmentation of macular optical coherence tomography images with serous pigment epithelial detachments. IEEE transactions on medical imaging, 34(2), 441--452.

Lee, K. E., Lee, K., Wahle, A., Meuer, S. M., Kulkarni, A., Klein, B. E., Sonka, M., Abramoff, M. D. & Klein, R. (2015). Axial length associations with retinal layer thicknesses from spectral domain optical coherent tomography (SD-OCT) macular scans in the Beaver Dam Eye Study (BDES). (Vols. 56). (7), pp. 906--906. Investigative Ophthalmology \& Visual Science.

Lee, K., Buitendijk, G. H., Bogunovic, H., Springelkamp, H., Hofman, A., Wahle, A., Sonka, M., Vingerling, J. R., Klaver, C. C. & Abramoff, M. D. (2015). Validation of Segmentability Index for Automated Prediction of Segmentation Reliability in SD-OCT Scans. (Vols. 56). (7), pp. 5292--5292. Investigative Ophthalmology \& Visual Science.

Miri, M. S., Bogunovic, H., Kwon, Y. H., Abramoff, M. D., Sonka, M. & Garvin, M. K. (2015). Minimum rim width better correlates with structural and functional measurements than horizontal rim width. (Vols. 56). (7), pp. 641--641. Investigative Ophthalmology \& Visual Science.

Xu, X., Lee, K., Zhang, L., Sonka, M. & Abramoff, Michael D, (2015). Stratified sampling voxel classification for segmentation of intraretinal and subretinal fluid in longitudinal clinical OCT data. IEEE transactions on medical imaging, 34(7), 1616--1623.

Woo, V., Chen, Z., Hirai, T., Weber, J. R., Kovarnik, T., Wahle, A., Sonka, M. & Lopez, J. J. (2015). An Automated Computational Method for Quantification of Total Fibrous Cap Volume and Mean Fibrous Cap Thickness with Optical Coherence Tomography. (Vols. 15). (66), pp. B143--B144. Journal of the American College of Cardiology.

Klein, B. E., Johnson, C. A., Meuer, S. M., Lee, K., Wahle, A., Lee, K. E., Kulkarni, A., Sonka, M., Abramoff, M. D. & Klein, R. (2015). Spectral domain optical coherence tomography (SD-OCT) and characteristics associated with glaucoma in community living older adults. (Vols. 56). (7), pp. 626--626. Investigative Ophthalmology \& Visual Science.

Zhang, L., Wahle, A., Chen, Z., Zhang, L., Downe, R. W., Kovarnik, T. & Sonka, M. (2015). Simultaneous registration of location and orientation in intravascular ultrasound pullbacks pairs via 3D graph-based optimization. IEEE transactions on medical imaging, 34(12), 2550--2561.

Bogunovic, H., Sonka, M., Zhang, L. & Abramoff, M. D. (2015). Prediction of Future Visual Acuity from OCT Images during Anti-VEGF Induction Phase in Patients with Exudative Age-Related Macular Degeneration. (Vols. 56). (7), pp. 1519--1519. Investigative Ophthalmology \& Visual Science.

Wahle, A., Lee, K. E., Lee, K., Zhang, L., Bogunovic, H., Harding, A. T., Scheetz, T. E., Sonka, M., Klein, R. & Abramoff, M. D. (2015). Use of XNAT to generate phenotype data from OCT scans for use with genetic association analyses. (Vols. 56). (7), pp. 1261--1261. Investigative Ophthalmology \& Visual Science.

Abramoff, M. D., Bogunovic, H., Kwon, Y. H., Critser, B., Garvin, M. K. & Sonka, M. (2015). Repeatability of Automated OCT-based 24-2 Visual Threshold Estimationin Patients with Glaucoma. (Vols. 56). (7), pp. 1696--1696. Investigative Ophthalmology \& Visual Science.

Zhang, L., Sohn, E. H., Mullins, R. F., Sonka, M. & Abramoff, M. D. (2015). Automated quantification of choriocapillaris thickness near drusen. (Vols. 56). (7), pp. 5141--5141. Investigative Ophthalmology \& Visual Science.

Oguz, I., Styner, M., Sanchez, M., Shi, Y. & Sonka, M. (2015). LOGISMOS-B for Primates: Primate Cortical Surface Reconstruction and Thickness Measurement. (Vols. 9413). Proceedings of SPIE. PMID: 26028802.

Almeida, D. R., Zhang, L., Chin, E. K., Mullins, R. F., Kucukevcilioglu, M., Critser, D. B., Sonka, M., Stone, E. M., Folk, J. C., Abràmoff, M. D. & Russell, S. R. (2015). Comparison of retinal and choriocapillaris thicknesses following sitting to supine transition in healthy individuals and patients with age-related macular degeneration. JAMA ophthalmology, 133(3), 297-303. PMID: 25521616.

Zhang, L., Buitendijk, G. H., Lee, K., Sonka, M., Springelkamp, H., Hofman, A., Vingerling, J. R., Mullins, R. F., Klaver, C. C. & Abràmoff, M. D. (2015). Validity of Automated Choroidal Segmentation in SS-OCT and SD-OCT. Investigative ophthalmology & visual science, 56(5), 3202-3211. PMID: 26024104.

Chen, H., Chen, X., Qiu, Z., Xiang, D., Chen, W., Shi, F., Zheng, J., Zhu, W. & Sonka, M. (2015). Quantitative analysis of retinal layers' optical intensities on 3D optical coherence tomography for central retinal artery occlusion. (Vols. 5). pp. 9269. Scientific reports. PMID: 25784298.

Kafieh, R., Rabbani, H., Hajizadeh, F., Abramoff, M. D. & Sonka, M. (2015). Thickness mapping of eleven retinal layers segmented using the diffusion maps method in normal eyes. Journal of ophthalmology, 2015, 259123. PMID: 25960888.

Oguz, I., Zhang, L., Lee, K., Abramoff, M. D. & Sonka, M. (2015). 4D longitudinal choroidal thickness quantification improves reproducibility. (Vols. 56). (7), pp. 5288--5288. Investigative Ophthalmology \& Visual Science.

Zhang, L., Wahle, A., Chen, Z., Lopez, J., Kovarnik, T. & Sonka, M. (2015). Prospective prediction of thin-cap fibroatheromas from baseline virtual histology intravascular ultrasound data. In International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 603--610.

Meuer, S. M., Lee, K., Wahle, A., Lee, K. E., Kulkarni, A., Klein, B. E., Sonka, M., Abramoff, M. D. & Klein, R. (2015). Age and sex distribution of retinal layer thickness from spectral domain optical coherence tomography (SD-OCT) macular scans in the Beaver Dam Eye Study (BDES). (Vols. 56). (7), pp. 1805--1805. Investigative Ophthalmology \& Visual Science.

Choi, C., Zhang, L., Abramoff, M. D., Sonka, M., Shifera, A. & Kay, C. N. (2014). Efficacy of Aflibercept in Refractory Wet Age-Related Macular Degeneration. Investigative Ophthalmology \& Visual Science, 55(13), 3936--3936.

Bogunovic, Hrvoje,, Sonka, M., Kwon, Y. H., Kemp, P., Abramoff, Michael D, & Wu, X. (2014). Multi-surface and multi-field co-segmentation of 3-D retinal optical coherence tomography. IEEE transactions on medical imaging, 33(12), 2242--2253.

Bogunovic, H., Abramoff, M. D., Wu, X., Kemp, P. S., Garvin, M. K., Alward, W. L., Fingert, J. H., Kwon, Y. H. & Sonka, M. (2014). Mosaicing and Multi-Field Layer Segmentation of 3D Retinal OCT. Investigative Ophthalmology \& Visual Science, 55(13), 4813--4813.

Miri, M. S., Kwon, Y. H., Wang, J., Abramoff, M. D., Sonka, M. & Garvin, M. K. (2014). Computing the Minimum Rim Width: Should the Border Tissue Be Considered?. Investigative Ophthalmology \& Visual Science, 55(13), 4750--4750.

Oguz, I., Sonka, M. (2014). Robust cortical thickness measurement with LOGISMOS-B. In International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 722--730.

Lee, K., Buitendijk, G. H., Springelkamp, H., Sonka, M., Vingerling, J. R., Klaver, C. C. & Abramoff, M. D. (2014). Relationship between Intensity Based Image Quality Indices of Retinal SD-OCT and Performance of Automated Retinal Layer Segmentation. Investigative Ophthalmology \& Visual Science, 55(13), 4789--4789.

Wahle, A., Harding, A. T., Lee, K., Garvin, M. K., Alward, W. L., Fingert, J. H., Kopel, T. R., Abramoff, M. D., Kwon, Y. H. & Sonka, M. (2014). Supporting Glaucoma Structure/Function Research with a Unified OCT, Fundus, and Visual Field Database. Investigative Ophthalmology \& Visual Science, 55(13), 4821--4821.

Zhang, L., Downe, R., Chen, Z., Sun, S., Masiarov, T., Kovarnik, T., Lopez, J., Sonka, M. & Wahle, A. (2014). Side-branch guided registration of intravascular ultrasound pullbacks in coronary arteries. In MICCAI Workshop in Computing and Visualization for IntraVascular Imaging and Computer Assisted Stenting (CVII-STENT). pp. 44--51.

Oguz, I., Sonka, M. (2014). LOGISMOS-B: layered optimal graph image segmentation of multiple objects and surfaces for the brain. IEEE transactions on medical imaging, 33(6), 1220--1235.

Zhang, L., Abramoff, M. D., Waldstein, S. M., Gerendas, B., Glodan, A., Simader, C., Schmidt-Erfurth, U. & Sonka, M. (2014). Reproducibility of automated choroidal thickness measurements: swept-source OCT and spectral-domain OCT using enhanced depth imaging. Investigative Ophthalmology \& Visual Science, 55(13), 4796--4796.

Rashid, A., Schmidt-Erfurth, U., Gerendas, B., Waldstein, S. M., Wahle, A., Simader, C., Lee, K., Wang, K., Sonka, M. & Abramoff, M. D. (2014). Reproducibility of Total Retinal Thickness in 5 SD-OCT Scanners using Iowa Reference Algorithm. Investigative Ophthalmology \& Visual Science, 55(13), 4786--4786.

Oguz, I., Zhang, H., Rumple, A. & Sonka, M. (2014). RATS: Rapid Automatic Tissue Segmentation in rodent brain MRI. Journal of neuroscience methods, 221, 175-182. PMID: 24140478.

Bogunovic, H., Kwon, Y. H., Rashid, A., Lee, K., Critser, D. B., Garvin, M. K., Sonka, M. & Abràmoff, M. D. (2014). Relationships of retinal structure and humphrey 24-2 visual field thresholds in patients with glaucoma. Investigative ophthalmology & visual science, 56(1), 259-271. PMID: 25491294.

Sonka, M., Hlavac, V. & Boyle, R. (2014). Image Processing, Analysis, and Machine Vision - 4th Ed. (Vols. 890). New York: Cengage Learning.

Gerendas, B. S., Waldstein, S. M., Simader, C., Deak, G., Hajnajeeb, B., Zhang, L., Bogunovic, H., Abramoff, M. D., Kundi, M., Sonka, M. & Schmidt-Erfurth, U. (2014). Three-dimensional automated choroidal volume assessment on standard spectral-domain optical coherence tomography and correlation with the level of diabetic macular edema. American journal of ophthalmology, 158(5), 1039-1048. PMID: 25127697.

Zhang, L., Sonka, M., Folk, J. C., Russell, S. R. & Abràmoff, M. D. (2014). Quantifying disrupted outer retinal-subretinal layer in SD-OCT images in choroidal neovascularization. Investigative ophthalmology & visual science, 55(4), 2329-35. PMID: 24569576.

Rabbani, H., Sonka, M. & Abramoff, M. D. (2013). Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain. International journal of biomedical imaging, 2013, 417491. PMID: 24222760.

Zhang, H., Abiose, A. K., Gupta, D., Campbell, D. N., Martins, J. B., Sonka, M. & Wahle, A. (2013). Novel indices for left-ventricular dyssynchrony characterization based on highly automated segmentation from real-time 3-d echocardiography. (Vols. 39). (1), pp. 72-88. Ultrasound Med Biol. PMID: 23141901.

Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Finet, J., Fillion-Robin, J., Pujol, S., Bauer, C., Jennings, D., Fennessy, F., Sonka, M., Buatti, J., Aylward, S., Miller, J., Pieper, S. & Kikinis, R. (2012). 3D Slicer As An Image Computing Platform For The Quantitative Imaging Network. Magnetic Resonance Imaging, 30(9), 1323-1341. PMID: 22770690.

Zhang, L., Lee, K., Niemeijer, M., Mullins, R. F., Sonka, M. & Abramoff, M. D. (2012). Automated Segmentation of the Choroid from Clinical SD-OCT. Invest Ophthalmol Vis Sci, 53(12), 7510-9. PMID: 23060139.

Xu, L., Stojkovic, B., Zhu, Y., Song, Q., Wu, X., Sonka, M. & Xu, J. (2011). Efficient algorithms for segmenting globally optimal and smooth multi-surfaces. Information processing in medical imaging, 22, 208-220. PMID: 21761658.

Antony, B., Abramoff, M. D., Tang, L., Ramdas, W. D., Vingerling, J. R., Jansonius, N. M., Lee, K., Kwon, Y. H., Sonka, M. & Garvin, M. K. (2011). Automated 3-D method for the correction of axial artifacts in spectral-domain optical coherence tomography images. Biomed Opt Express, 2(8), 2403-16. PMID: 21833377.

Abramoff, M., Garvin, M. & Sonka, M. (2010). Retinal Imaging and Image Analysis. IEEE Reviews in Biomedical Engineeringÿ, 3, 169-208.

Sonka, M., Hlavac, V. & Boyle, R. (2007). Image Processing, Analysis, and Machine Vision - 3rd Ed. pp. 850 pages. Thomson Engineering, Toronto, Canada.

Li, K., Wu, X., Chen, D. Z. & Sonka, M. (2006). Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach. IEEE Trans Pattern Anal Mach Intell, 28(1), 119-134. PMID: 16402624.

Christensen, G. E., Sonka, M. (2005). Information Processing in Medical Imaging, Proceedings (series: Lecture Notes in Computer Science Vol. 3565). Springer, Berlin.

Sonka, M., Fitzpatrick, J. M. (2000). Handbook of Medical Imaging Volume 2 - Medical Image Processing and Analysis. pp. 1250 pages. SPIE.