Publications

My publications on Google Scholar and DBLP.

All publications in one bibtex file.

Journal Papers

  1. Franc, V., Fikar, O., Bartos, K., Sofka, M., 2018. Learning data discretization via convex optimization. Machine Learning 333–355.


  2. Sofka, M., Zhang, J., Good, S., Zhou, S.K., Comaniciu, D., 2014. Automatic Detection and Measurement of Structures in Fetal Head Ultrasound Volumes Using Sequential Estimation and Integrated Detection Network (IDN). IEEE Transactions on Medical Imaging 33, 1054–1070.


  3. Lin, K.-S., Tsai, C.-L., Tsai, C.-H., Sofka, M., Chen, S.-J., Lin, W.-Y., 2012. Retinal Vascular Tree Reconstruction With Anatomical Realism. IEEE Transactions on Biomedical Engineering 59, 3337–3347.


  4. Sofka, M., Ralovich, K., Zhang, J., Zhou, S.K., Comaniciu, D., 2012. Progressive Data Transmission for Anatomical Landmark Detection in a Cloud. Methods of Information in Medicine 51, 268–278.


  5. Sofka, M., V. Stewart, C., 2010. Location Registration and Recognition (LRR) for Serial Analysis of Nodules in Lung CT Scans. Medical Image Analysis 14, 407–428.


  6. Tsai, C.-L., Madore, B., Leotta, M., Sofka, M., Yang, G., Majerovics, A., L. Tanenbaum, H., V. Stewart, C., Roysam, B., 2008. Automated Retinal Image Analysis over the Internet. IEEE Transactions on Information Technology in Biomedicine 12, 480–487.


  7. Yang, G., V. Stewart, C., Sofka, M., Tsai, C.-L., 2007. Registration of Challenging Image Pairs: Initialization, Estimation, and Decision. Patern Analysis and Machine Intelligence 23, 1973–1989.


  8. Sofka, M., V. Stewart, C., 2006. Retinal Vessel Extraction Using Multiscale Matched Filters, Confidence and Edge Measures. IEEE Transactions on Medical Imaging 25, 1531–1546.


Book Chapters

  1. Sofka, M., 2015. Integrated Detection Network for Multiple Object Recognition. In: Zhou, S.K. (Ed.), Medical Image Recognition, Segmentation and Parsing. Elsevier.


  2. Birkbeck, N., Sofka, M., Kohlberger, T., Zhang, J., Wetzl, J., Kaftan, J., Zhou, S.K., 2014. Robust Segmentation of Challenging Lungs in CT using Multi-Stage Learning and Level Set Optimization. In: Suzuki, K. (Ed.), Computational Intelligence in Biomedical Imaging. Springer New York, pp. 185–208.


Unpublished Manuscripts

  1. Machlica, L., Sofka, M., Bartos, K., 2017. Learning detectors of malware behavior for intrusion detection in network traffic. ArXiv.


Conference Papers

  1. Sofka, M., Milletari, F., Jia, J., Rothberg, A., 2017. Fully convolutional regression network for accurate detection of measurement points. In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support (DLMIA). Quebec City, Quebec, Canada.


  2. Milletari, F., Rothberg, A., Jia, J., Sofka, M., 2017. Integrating statistical prior knowledge into convolutional neural networks. In: Proceedings of the 20th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2017). Quebec City, Quebec, Canada.


  3. Bartos, K., Sofka, M., Franc, V., 2016. Optimized Invariant Representation of Network Traffic for Detecting Unseen Malware Variants. In: USENIX Security Symposium. Austin, TX, USA.


  4. Bartos, K., Sofka, M., Franc, V., 2016. Learning Invariant Representation for Malicious Network Traffic Detection. In: Proceedings of the European Conference on Artificial Intelligence. Hague, Holland.


  5. Franc, V., Sofka, M., Bartos, K., 2015. Learning detector of malicious network traffic from weak labels. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Porto, Portugal, pp. 85–99.


  6. Bartos, K., Sofka, M., 2015. Robust representation of network traffic for detecting malware variations. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Porto, Portugal, pp. 116–132.


  7. Birkbeck, N., Kohlberger, T., Zhang, J., Sofka, M., Kaftan, J., Comaniciu, D., Zhou, S.K., 2014. Lung Segmentation from CT with Severe Pathologies Using Anatomical Constraints. In: Proceedings of the 17th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014). Boston, MA, USA.


  8. Wu, D., Sofka, M., Birkbeck, N., Zhou, S.K., 2014. Segmentation of Multiple Knee Bones from CT for Orthopedic Knee Surgery Planning. In: Proceedings of the 17th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014). Boston, MA, USA.


  9. El-Zehiry, N., Jolly, M.-P., Sofka, M., 2013. A Splice-Guided Data Driven Interactive Editing. In: International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2013). San Francisco, CA, USA.


  10. P. Harrison, A., Birkbeck, N., Sofka, M., 2013. IntellEditS: Intelligent Learning-Based Editor of Segmentations. In: Proceedings of the 16th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2013). Nagoya, Japan.


  11. Park, J.H., Sofka, M., Lee, S.M., Kim, D.Y., Zhou, S.K., 2013. Automatic Nuchal Translucency Measurement from Ultrasonography. In: Proceedings of the 16th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2013). Nagoya, Japan.


  12. Breitenreicher, D., Sofka, M., Britzen, S., Zhou, S.K., 2013. Hierarchical Discriminative Framework for Detecting Tubular Structures in 3D Images. In: Proceedings of the 23rd International Conference On Information Processing in Medical Imaging (IPMI 2013). Asilomar, CA, USA.


  13. Birkbeck, N., Sofka, M., Zhou, S.K., 2011. Fast Boosting Trees for Classification, Pose Detection, and Boundary Detection on a GPU. In: Proceedings of the 7th IEEE Workshop on Embedded Computer Vision (in Conjunction with IEEE CVPR). Colorado Springs, CO.


  14. Sofka, M., Ralovich, K., Birkbeck, N., Zhang, J., Zhou, S.K., 2011. Integrated Detection Network (IDN) for Pose and Boundary Estimation in Medical Images. In: Proceedings of the 8th International Symposium On Biomedical Imaging (ISBI 2011). Chicago, IL.


  15. Sofka, M., Wetzl, J., Birkbeck, N., Zhang, J., Kohlberger, T., Kaftan, J., Declerck, J., Zhou, S.K., 2011. Multi-stage Learning for Robust Lung Segmentation in Challenging CT Volumes. In: Proceedings of the 14th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011). Toronto, Canada.


  16. Sofka, M., Wu, D., Suehling, M., Liu, D., Tietjen, C., Soza, G., Zhou, S.K., 2011. Automatic Contrast Phase Estimation in CT Volumes. In: Proceedings of the 14th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011). Toronto, Canada.


  17. Kohlberger, T., Sofka, M., Zhang, J., Birkbeck, N., Wetzl, J., Kaftan, J., Declerck, J., and S. Kevin Zhou, 2011. Automatic Multi-Organ Segmentation Using Learning-based Segmentation and Level Set Optimization. In: Proceedings of the 14th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011). Toronto, Canada.


  18. Sofka, M., Zhang, J., Zhou, S.K., Comaniciu, D., 2010. Multiple Object Detection by Sequential Monte Carlo and Hierarchical Detection Network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). San Francisco, CA, USA.


  19. Sofka, M., Ralovich, K., Zhang, J., Zhou, S.K., Comaniciu, D., 2010. Progressive Data Transmission for Hierarchical Detection in a Cloud. In: Proceedings of the 2nd International Workshop on High-Performance Medical Image Computing for Image-Assisted Clinical Intervention and Decision-Making (HP-MICCAI 2010). Bejing, China.


  20. Lin, K.-S., Tsai, C.-L., Sofka, M., Tsai, C.-H., Chen, S.-J., Lin, W.-Y., 2009. Vascular Tree Construction with Anatomical Realism for Retinal Images. In: Bioinformatics and BioEngineering, 2009. BIBE ’09. Ninth IEEE International Conference On. pp. 313–318.


  21. Sofka, M., V. Stewart, C., 2008. Location Registration and Recognition (LRR) for Longitudinal Evaluation of Corresponding Regions in CT Volumes. In: Proceedings of the 11th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2008). pp. 989–997.


  22. Sofka, M., Yang, G., V. Stewart, C., 2007. Simultaneous Covariance Driven Correspondence (CDC) and Transformation Estimation in the Expectation Maximization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Minneapolis, MN, USA.


  23. Kelman, A., Sofka, M., Stewart, C.V., 2007. Keypoint Descriptors for Matching Across Multiple Image Modalities and Non-linear Intensity Variations. In: Proceedings of the IEEE Computer Vision and Pattern Recognition Workshop on Image Registration and Fusion. Minneapolis, MN, USA.


  24. Tsai, C.-L., Stewart, C.V., Perera, A., Lee, Y.-L., Yang, G., Sofka, M., 2006. A Correspondence-Based Software Toolkit for Image Registration. In: Proceedings of the IEEE International Conference On Systems, Man, and Cybernetics. Taipei, Taiwan, pp. 3972–3977.


  25. Yang, G., Stewart, C.V., Sofka, M., Tsai, C.-L., 2006. Automatic robust image registration system: initialization, estimation, and decision. In: Proceedings of the IEEE International Conference on Computer Vision Systems. New York, NY, pp. 23–31.


  26. Sofka, M., Benslimane, R., Macaire, L., Rudko, M., Postaire, J.-G., 2002. Archeological mosaic image indexing by color-based segmentation and skeleton extraction. In: Proceedings of the Second IEEE International Symposium on Signal Processing and Information Technology. Marrakesh, Marocco, pp. 327–331.


Granted


USPTO Granted
  1. Wu, D., Birkbeck, N., Sofka, M., Liu, M., Soza, G., & Zhou, S. K. (2017). Method and system for automatic pelvis unfolding from 3D computed tomography images. US9542741.
  2. Wu, D., Birkbeck, N., Sofka, M., Liu, M., & Zhou, S. K. (2016). Multi-Bone Segmentation for 3D Computed Tomography. US9495752.
  3. Bartos, K., & Sofka, M. (2016). Identifying Threats Based on Hierarchical Classification. US9462008.
  4. Bartos, K., Rehak, M., & Sofka, M. (2016). Global Clustering of Incidents Based on Malware Similarity and Online Trustfulness. US9432393.
  5. El-Zehiry, N. Y., Grady, L., Sofka, M., Tietjen, C., & Zhou, S. K. (2015). Semi-Automated Preoperative Resection Planning. US9129391.
  6. Sofka, M., Machlica, L., Bartos, K., & McGrew, D. (2015). Identifying Malware Communications with DGA Generated Domains by Discriminative Learning. US9781139.
  7. Kohlberger, T., Sofka, M., Wetzl, J., Zhou, J. Z. S. K., Birkbeck, N., Kaftan, J., & Declerck, J. (2015). Method and System for Multi-Organ Segmentation Using Learning-Based Segmentation and Level Set Optimization. US9042620.
  8. Sofka, M., Liu, M., Wu, D., & Zhou, S. K. (2014). Method and System for Bone Segmentation and Landmark Detection for Joint Replacement Surgery. US9646229.
  9. Sofka, M., Ralovich, K., Zhang, J., Zhou, S. K., Paladini, G., & Comaniciu, D. (2014). Data Transmission in Remote Computer Assisted Detection. US8811697.
  10. Birkbeck, N., Sofka, M., & Zhou, S. K. (2014). Method and System for Evaluation Using Probabilistic Boosting Trees. US8860715.
  11. Sofka, M., Zhang, J., Zhou, S. K., & Comaniciu, D. (2013). Method and System for Multiple Object Detection by Sequential Monte Carlo and Hierarchical Detection Network. US8605969.
  12. Zhang, L., Sofka, M., & Schäfer, U. (2012). Feature-Based Composing for 3D MR Angiography Images. US8265354.
  13. Sofka, M., Zhang, L., & Schäfer, U. (2010). Validation Scheme For Composing Magnetic Resonance Images (MRI). US7711161.

Pending


USPTO Applications
  1. Machlica, L., & Sofka, M. (2018). Joint Anomaly Detection Across IoT Devices. US20180041528.
  2. Jusko, J., & Sofka, M. (2018). Network Security Classification. US20180034838.
  3. Havelka, J., Sofka, M., & Rehak, M. (2017). Detection of malicious domains using recurring patterns in domain names. US20170295187.
  4. Franc, V., Bartos, K., & Sofka, M. (2017). Refined learning data representation for classifiers. US20170316342A1.
  5. Franc, V., Sofka, M., & Bartos, K. (2017). Learning Detector of Malicious Network Traffic from Weak Labels. US20170063893A1.
  6. Rothberg, A., de Jonge, M., Jia, J., Nouri, D., Rothberg, J. M., Sofka, M., … Gafner, T. (2017). Automated Image Analysis For Diagnosing A Medical Condition. US20170360412.
  7. Gafner, T., de Jonge, M., Schneider, R., Elgena, D., Rothberg, A., Rothberg, J. M., … Thiele, K. (2017). Augmented Reality Interface For Assisting A User To Operate An Ultrasound Device. US20170360404.
  8. Rothberg, A., de Jonge, M., Jia, J., Nouri, D., Rothberg, J. M., & Sofka, M. (2017). Automated Image Analysis For Identifying A Medical Parameter. US20170360411.
  9. Rothberg, A., de Jonge, M., Jia, J., Nouri, D., Rothberg, J. M., & Sofka, M. (2017). Automated Image Acquisition For Assisting A User To Operate An Ultrasound Device. US20170360403.
  10. Bartos, K., & Sofka, M. (2015). Robust Representation of Network Traffic for Detecting Malware Variations. US20170063892.
  11. Machlica, L., & Sofka, M. (2015). Hierarchical Feature Extraction for Malware Classification in Network Traffic. US20170134404.
  12. Zhou, S. K., Birkbeck, N., Guardia, G. D., Zhang, J., Sofka, M., B. Thompson, J., & Paladini, G. (2014). Cloud-Based Processing of Medical Imaging Data. US20160092632.