Sökning: "Organs at risk"
Visar resultat 6 - 10 av 73 uppsatser innehållade orden Organs at risk.
6. Incidens av hypoxemi och hypotension hos hund under anestesi vid kejsarsnitt : djursjukskötarens roll i förebyggande omvårdnad
Uppsats för yrkesexamina på grundnivå, SLU/Dept. of Clinical SciencesSammanfattning : Uppskattningsvis 26 % av dräktiga tikar drabbas av dystoki. Åtgärder för dystoki inkluderar kejsarsnitt, medicinsk behandling och manuell korrigering. Den bakomliggande orsaken avgör lämplig behandling men i 50–65 % av fallen behöver tiken förlösas med kejsarsnitt. LÄS MER
7. COMPARISON OF MULTI-CRITERIA OPTIMIZATION IN TWO DIFFERENT TREATMENT PLANNING SYSTEMS
Master-uppsats,Sammanfattning : Purpose: The purpose with this study was to compare multi-criteria optimization (MCO) for volumetric modulated arc therapy (VMAT) treatment plans in two different treatment planning systems. Theory: When performing treatment planning prior to radiation therapy it is important to prioritize between absorbed dose to target and absorbed dose to organs at risk (OAR). LÄS MER
8. APOPTOTIC EFFECTS IN RENAL CORTEX AFTER TREATMENT WITH 177LU-OCTREOTATE
Master-uppsats,Sammanfattning : Purpose: The purpose of this project was to investigate gene regulation of a predetermined panel of apoptotic genes in murine renal cortex after treatment with 177Lu-octreotate after one day and seven days. Theory: The kidneys and bone marrow are the risk organs in 177Lu-octreotate treatment, but by fractioning the treatment the bone marrow recovers. LÄS MER
9. Image Processing in MRI Guided Real-TimeAdaptive Radiotheraphy - Upsampling and Segmentation of Target Volume and Organs at Risk
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Magnetic Resonance Imaging (MRI) is a useful medical imaging technique that is used for cancer treatment.The major drawback of this method is the relatively long scan time, limiting its use for real time tracking of a potentially moving target during the radiotherapy session. LÄS MER
10. Deep-learning based prediction model for dose distributions in lung cancer patients
Master-uppsats, Stockholms universitet/FysikumSammanfattning : Background To combat one of the leading causes of death worldwide, lung cancer treatment techniques and modalities are advancing, and the treatment options are becoming increasingly individualized. Modern cancer treatment includes the option for the patient to be treated with proton therapy, which can in some cases spare healthy tissue from excessive dose better than conventional photon radiotherapy. LÄS MER