Analysis of surgeon's performance during training of surgical suturing from video

Tato práce se zabývá tvorbou algoritmu, který bude schopen detekovat určité medicínské nástroje (jehelec, pinzetu, nůžky) z obrazu. Další algoritmus bude schopen detekovat různé objekty v obraze, tato detekce bude použita k předzpracování videa. Společně tyto detekce vytvoří pro uživatel statistiku a ohodnocení výkonu. Nejprve jsou shrnuté současné přístupy ke zpracování obrazu. Dále jsou popsány datasety potřebné k trénování neuronových sítí. Poslední část se věnuje ověření funkčnosti natrénovaných neuronových sítí.ObhájenoThe focus of this bachelor thesis is to develop an algorithm that will be able to detect certain medical instruments (needle holder, tweezers, scissors) from an image. Another algorithm will be able to detect different objects in the image, this detection will be used to pre-process the video. Together these detections will produce statistics and performance ratings for the user. First, the current approaches to image processing are summarized. Next, the datasets needed to train the neural networks are described. The last section is devoted to validating the performance of the trained neural networks

Analysis of surgeon's performance during training of surgical suturing from video

Tato práce se zabývá tvorbou algoritmu, který bude schopen detekovat určité medicínské nástroje (jehelec, pinzetu, nůžky) z obrazu. Další algoritmus bude schopen detekovat různé objekty v obraze, tato detekce bude použita k předzpracování videa. Společně tyto detekce vytvoří pro uživatel statistiku a ohodnocení výkonu. Nejprve jsou shrnuté současné přístupy ke zpracování obrazu. Dále jsou popsány datasety potřebné k trénování neuronových sítí. Poslední část se věnuje ověření funkčnosti natrénovaných neuronových sítí.ObhájenoThe focus of this bachelor thesis is to develop an algorithm that will be able to detect certain medical instruments (needle holder, tweezers, scissors) from an image. Another algorithm will be able to detect different objects in the image, this detection will be used to pre-process the video. Together these detections will produce statistics and performance ratings for the user. First, the current approaches to image processing are summarized. Next, the datasets needed to train the neural networks are described. The last section is devoted to validating the performance of the trained neural networks

Nursing Process for a Patient with Post-resuscitation Therapeutic Hypothermia after Acute Myocardial Infarction

The bachelor's thesis deals with acute cardiology, namely with casuistry of a patient after acute myocardial infarction with successful cardiopulmonary resuscitation in the field, artificial pulmonary ventilation and therapeutic hypothermia. The thesis wants to present the highly specialised and demanding nursing care of resuscitated patients from the nurse's point of view with the use of the most modern procedures and technology. The theoretical part of the thesis is divided to several chapters describing anatomy and physiology of the cardiac muscle, acute myocardial infarction, cardiopulmonary resuscitation and therapeutic hypothermia. The main focus of this part of the thesis is on the diagnosis of the acute coronary syndrom itself. The theoretical part describes in more detail therapeutic hypothermia and nursing care of patients after cardiopulmonary resuscitation. Very important chapter is also introduction of a patient on whom is concentrated the nursing care in the practical part of the thesis, and presentation of his hospitalization. The practical part deals with creating, planning and implementation of the nursing care by means of biomedical model and nursing process. The practical and theoretical part alike is divided to several chapters. The main one is focused on nursing anamnesis with..

Evolution of chain migration in an aerial insectivorous bird, the common swift Apus apus

Spectacular long-distance migration has evolved repeatedly in animals enabling exploration of resources separated in time and space. In birds, these patterns are largely driven by seasonality, cost of migration, and asymmetries in competition leading most often to leap-frog migration, where northern breeding populations winter furthest to the south. Here we show that the highly aerial common swift Apus apus, spending the non-breeding period on the wing, instead exhibits a rarely-found chain migration pattern, where the most southern breeding populations in Europe migrate to wintering areas furthest to the south in Africa, while the northern populations winter to the north. The swifts concentrated in three major areas in sub-Saharan Africa during the non-breeding period, with substantial overlap for nearby breeding populations. We found that the southern breeding swifts were larger, raised more young, and arrived to the wintering areas with higher seasonal variation in greenness (Normalized Difference Vegetation Index, NDVI) earlier than the northern breeding swifts. This unusual chain migration pattern in common swifts is largely driven by differential annual timing and we suggest it evolves by prior occupancy and dominance by size in the breeding quarters and by prior occupancy combined with diffuse competition in the winter.,Average winter position in November and December fo rindividually tracked common swifts (Apus apus) breeding in Europe. Tracking method geolocation by light. Clutch size measured as maximum number of young in nest. Wing and mass of common swifts breeding in Europe. Wing and mass collected during ringing at breeding sites.