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Detection of foreign objects in X-ray chest images using machine learning methods
Matoušková, Barbora ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
Foreign objects in Chest X-ray (CXR) cause complications during automatic image processing. To prevent errors caused by these foreign objects, it is necessary to automatically find them and ommit them in the analysis. These are mainly buttons, jewellery, implants, wires and tubes. At the same time, finding pacemakers and other placed devices can help with automatic processing. The aim of this work was to design a method for the detection of foreign objects in CXR. For this task, Faster R-CNN method with a pre-trained ResNet50 network for feature extraction was chosen which was trained on 4 000 images and lately tested on 1 000 images from a publicly available database. After finding the optimal learning parameters, it was managed to train the network, which achieves 75% precision, 77% recall and 76% F1 score. However, a certain part of the error is formed by non-uniform annotations of objects in the data because not all annotated foreign objects are located in the lung area, as stated in the description.
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Electrotechnical production mapping and improvement
Kutnar, Pavel ; Starý, Jiří (referee) ; Špinka, Jiří (advisor)
This thesis is an introduction into quality management of electrotechnical production. It consists of a theoretical treatise on FMEA analysis and process mapping. The FMEA analysis was applied to the manufacturing process in an electrotechnical company. Selected critical failures were analyzed and corrective measures were suggested.
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Detection of foreign objects in X-ray chest images using machine learning methods
Matoušková, Barbora ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
Foreign objects in Chest X-ray (CXR) cause complications during automatic image processing. To prevent errors caused by these foreign objects, it is necessary to automatically find them and ommit them in the analysis. These are mainly buttons, jewellery, implants, wires and tubes. At the same time, finding pacemakers and other placed devices can help with automatic processing. The aim of this work was to design a method for the detection of foreign objects in CXR. For this task, Faster R-CNN method with a pre-trained ResNet50 network for feature extraction was chosen which was trained on 4 000 images and lately tested on 1 000 images from a publicly available database. After finding the optimal learning parameters, it was managed to train the network, which achieves 75% precision, 77% recall and 76% F1 score. However, a certain part of the error is formed by non-uniform annotations of objects in the data because not all annotated foreign objects are located in the lung area, as stated in the description.
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Electrotechnical production mapping and improvement
Kutnar, Pavel ; Starý, Jiří (referee) ; Špinka, Jiří (advisor)
This thesis is an introduction into quality management of electrotechnical production. It consists of a theoretical treatise on FMEA analysis and process mapping. The FMEA analysis was applied to the manufacturing process in an electrotechnical company. Selected critical failures were analyzed and corrective measures were suggested.
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