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.