Publikációk

 Első munkaszakasz (2015.10.01-2016.09.30.)

[1] B. Antal: Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks, International Conference on Signal Processing and Communication Systems (SPCS 2016), Lisbon, Portugal, accepted.

[2] L. Kovacs, S. Petr, L. Riha: HPC GPU/CPU társkártyákkal támogatott fotorealisztikus 3D CT vizualizáció, In: Szirmay-Kalos László, Renner Gábor (szerk.), 8th Hungarian Conference on Computer Graphics and Geometry, Budapest, 2016, 175-180. (in Hungarian)

[3] L. Kovacs: Applications of the High Performance Computing in Medical Imaging and Visualization, The seventh International HPC summer school on HPC Challenges in Computer Sciences (IHPCSS), Ljubljana, Slovenia, 2016.

[4] L. Kovacs: Photorealistic 3D CT visualization supported by HPC GPU and CPU coprocessors, GPU Day 2016 – The Future Of Many-Core Computing In Science, Budapest, Hungary, 2016.

[5] J. Toth, L. Bartha, T. Szabo, I. Lazar, B. Harangi, A. Hajdu: An Online Application for Storing, Analyzing, and Sharing Dermatological Data, 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2015), Gyor. Hungary, 339-342.

Második munkaszakasz (2016.10.01-2017.09.30.)

[6] B. Harangi, A. Hajdu, R. Lampe, P. Torok: Recognizing ureter and uterine artery in endoscopic images using a convolutional neural network, 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2017), Thessaloniki, Greece, 2017, pp. 726-727.

[7] M. Pap, B. Harangi, A. Hajdu: Automatic Pigment Network Classification Using a Combination of Classical Texture Descriptors and CNN Features, 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2017), Thessaloniki, Greece, 2017, pp. 343-748.

[8] A. Tiba, B. Harangi, A. Hajdu: Efficient Texture Regularity Estimation for Second Order Statistical Descriptors, 10th International Symposium on Image and Signal Processing and Analysis (ISPA 2017), Ljubljana, Slovenia, pp. 90-94, 2017.

[9] P. Burai, B. Harangi: Pixelwise segmentation of uterine wall in endoscopic video frame using convolutional neural networks, 10th International Symposium on Image and Signal Processing and Analysis (ISPA 2017), Ljubljana, Slovenia, pp. 95-98., 2017.

[10] B. Harangi, A. Hajdu, P. Torok, R. Lampe: Differentiating ureter and arteries in the pelvic area via endoscope camera using deep neural network, 10th International Symposium on Image and Signal Processing and Analysis (ISPA 2017), Ljubljana, Slovenia, pp. 86-89, 2017.

Harmadik munkaszakasz (2017.10.01-2018.09.30.)

[11] D. Barath: Approximate epipolar geometry from six rotation invariant correspondences, 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2018), Funchal-Madeira, Portugal, pp. 464-471.

[12] D. Barath, J. Matas: Graph-Cut RANSAC, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), Prague, Czech Republic, pp. 6733-6741.

[13] D. Barath: Five-point Fundamental Matrix Estimation for Uncalibrated Cameras, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), Prague, Czech Republic

[14] D. Barath: Efficient energy-based topological outlier rejection, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), Prague, Czech Republic, pp. 70-81.

[15] P. Burai, A. Hajdu, FE Manuel, B. Harangi: Segmentation of the uterine wall by an ensemble of fully convolutional neural networks, Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference (EMBC 2018), Honolulu, Hi, pp. 49-52

[16] B. Benyo, B. Palancz, A. Szlavecz, S. Kent, J. Homlok, C. G.Pretty, J. G. Chase: Unsupervised Classification based Analysis of the Temporal Pattern of Insulin Sensitivity and Modelling Noise of Patient Groups under Tight Glycemic Control, 10th IFAC Symposium on Biological and Medical Systems BMS 2018, São Paulo, Brazil, pp. 62-67

[17] T. Umenhoffer: An anatomical aortic root model based on N-sided patches for elastic simulation, IX. Magyar Számítógépes Grafika és Geometria Konferencia, Budapest, 2018. pp. 143-149.

[18] A. Kacso, László Szécsi, Márton Tóth, Balázs Benyó, Tamás Umenhoffer: Finite volume blood flow simulation for highly deformable boundaries. Proceedings of the Workshop on the Advances of Information Technology: WAIT 2018. Budapest. pp. 55-60.

[19] M. Toth, T. Umenhoffer, L Szecsi, A. Kacso, B. Benyo: Aortic Root Simulation Using Smoothed Particle Hydrodynamics, WAIT: Workshop on the Advances in Information Technology, Budapest

[20] T. Umenhoffer, M. Toth, L. Szecsi, A. Kacso, B. Benyo: Aortic root simulation framework for valve sparing aorticroot replacement surgery, WAIT: Workshop on the Advances in Information Technology, Budapest

[21] T. Umenhoffer, M. Toth, ⁎A. Kacso, L. Szecsi, A. Szlavecz, P. Somogyi, L. Szilagyi, A. Kubovje, T. Szerafin, L. Szirmay-Kalos, B.Benyo: Modeling and simulation framework of aortic valve for hemodynamic evaluation of aortic root replacement surgery outcomes, 10th IFAC Symposium on Biological and Medical SystemsSão Paulo, Brazil, pp. 258-263