09:00-09:50 | General Lecture II
Chair: Arkadiusz Or³owski | 09:50-10:00 | Coffee break | 10:00-11:20 | Session III. Biomedical applications
Chair: Joanna Jaworek-Korjakowska
1 Software for CT-image analysis to assist the choice of mechanical-ventilation settings in acute respiratory distress syndrome Eduardo E. Dįvila Serrano CNRS, Franēois Dhelft Univ. Lyon 1 - Hospices Civils de Lyon, Laurent Bitker Univ. Lyon 1 - Hospices Civils de Lyon, Jean-Christophe Richard Univ. Lyon 1 - Hospices Civils de Lyon, Maciej Orkisz Univ. Lyon 1, CREATIS, France |  show paper details | 
2 Tuberculosis Abnormality Detection in Chest X-Rays: A Deep Learning Approach Mustapha Oloko-Oba, Serestina ViririTuberculosis Chest X-ray, Classification, Deep Learning, Pulmonary, Convolutional Neural Network Tuberculosis has claimed many lives, especially in developing countries. While treatment is possible, it requires an accurate diagnosis first to detect the presence of tuberculosis. Several screening techniques exist and the most reliable is the chest X-ray but the necessary radiological expertise for accurately interpreting the chest X-ray images is lacking. The task of manual examination of large chest X-ray images by the radiologist is time-consuming and could result in misdiagnosis as a result of a lack of expertise. Hence, a computer-aided diagnosis could
perform this task quickly, accurately and drastically improve the ability to diagnose correctly and ultimately treat the disease earlier. As a result of the complexity that surrounds the manual diagnosis of chest X-ray, we propose a model that employs the use of learning algorithm
(Convolutional Neural Network) to effectively learn the features associated with tuberculosis and make corresponding accurate predictions. Our model achieved 87.8% accuracy in classifying chest X-ray into abnormal and normal classes and validated against the ground-truth. Our model expresses a promising pathway in solving the diagnosis issue in early
detection of tuberculosis manifestation and hope for the radiologist and medical healthcare facilities in the developing countries. |  hide paper details | 
3 On the Effect of DCE MRI Slice Thickness and Noise on Estimated Pharmacokinetic Biomarkers - A Simulation Study Jakub Jurek, Lars A. Reisæter, Marek Kociński, Andrzej Materka |  show paper details | 
4 Nuclei detection with local threshold processing in DAB&H stained breast cancer biopsy images Lukasz Roszkowiak (IBIB PAN), Jakub Zak (IBIB PAN), Krzysztof Siemion (IBIB PAN), Dorota Pijanowska (IBIB PAN), Anna Korzynska (IBIB PAN) |  show paper details |
| 10:20-13:00 | Lunch break | 13:00-14:20 | Session IV. 3D vision
Chair: Andrzej ¦luzek
1 Performance Evaluation of Selected 3D Keypoint Detector-Descriptor Combinations Paula Stancelova, Elena Sikudova, Zuzana Cernekova |  show paper details | 
2 A vision based hardware-software real-time control system for the autonomous landing of an UAV Krzysztof Blachut, Hubert Szolc, Mateusz Wasala, Tomasz Kryjak, Marek Gorgon, AGH University of Science and Technology, Krakow, Poland |  show paper details | 
3 RGB-D and Lidar Calibration Supported by GPU Artur Wilkowski, Warsaw University of Technology and Dariusz Mańkowski, United Robots |  show paper details | 
4 Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking Dominika Przewlocka, Mateusz Wasala, Hubert Szolc, Krzysztof Blachut, Tomasz Kryjak - AGH University of Science and Technology, Krakow, Poland |  show paper details |
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