Blar i Brage NMBU på forfatter "Futsæther, Cecilia Marie"
-
Exploration of LET dependent effects in proton beam therapy using machine learning analysis of TL glow curves from CaSO4:Tm and LTB:Cu
Eriksen, Erling Ween (Master thesis, 2023)This thesis describes an investigation into the depth-dependent effects in proton radiation, evaluated by the use of Thermoluminescence Dosimetry (TLD) with CaSO4:Tm and LTB:Cu as target materials. Data collected on these ... -
Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics
Huynh, Bao Ngoc; Grøndahl, Aurora Rosvoll; Tomic, Oliver; Liland, Kristian Hovde; Knudtsen, Ingerid Søberg Skjei; Hoebers, Frank; van Elmpt, Wouter; Malinen, Eirik; Dale, Einar; Futsæther, Cecilia Marie (Peer reviewed; Journal article, 2023) -
Identification of biomarkers from Radiomics of brain scans for prediction of major depression using Repeated Elastic Net Technique
Shah, Krishna Mohan (Master thesis, 2022)The application of machine learning in the field of medicine is expanding on an almost daily basis. Data from the healthcare industry typically have high dimensionality but a limited sample size. The learning process can ... -
Image processing, radiomics and model selection for prediction of treatment outcome of anal cancer using CT-, PET-, and MR-sequences
Cabrol, Maria Francoise Olaug Odette H. (Master thesis, 2019)The goal of this master thesis was to predict treatment outcome of anal cancer using features extracted from medical image sequences. The medical images had beforehand been provided from and registered at the Norwegian ... -
In Quest of the Alanine R3 Radical: Multivariate EPR Spectral Analyses of X‑Irradiated Alanine in the Solid State
Jåstad, Eirik Ogner; Torheim, Turid K Gjerstad; Villeneuve, Kathleen; Kvaal, Knut; Hole, Eli Olaug; Sagstuen, Einar; Malinen, Eirik; Futsæther, Cecilia Marie (Journal article; Peer reviewed, 2017)The amino acid L-α-alanine is the most commonly used material for solidstate electron paramagnetic resonance (EPR) dosimetry, due to the formation of highly stable radicals upon irradiation, with yields proportional to the ... -
Machine learning for detecting biomarkers of Alzheimer’s disease : data-centric approach with dynamic ensemble selection
Naqvi, Muhammad Muntazir (Master thesis, 2022)Alzheimer’s disease (AD) is a neurodegenerative disorder that progresses over time and results in gradual loss of cognitive abilities. It affects the patient to an extent that they become unable to perform daily routine ... -
Predicting patient outcome using radioclinical features selected with RENT for patients with colorectal cancer
Engesæth, Lars Jetmund Svartis (Master thesis, 2022)Colorectal cancer remains a problem in medicine, costing countless lives each year. The growing amount of data available about these patients have piqued the interest of researchers, as they try to use machine learning to ... -
Predictive machine learning on SEM and hyperspectral images of uranium ore concentrates (UOCs) for nuclear forensics
Lande, Isak Biringvad (Master thesis, 2020)Nuclear and radioactive materials are harmful to individuals, especially when it’s not professionally managed. Nuclear and radioactive materials going astray pose a great threat to the general public. The field of nuclear ... -
Prediksjon av behandlingsutfall for hode- og halskreft ved bruk av radiomics av PET/CT-bilder
Midtfjord, Alise Danielle (Master thesis, 2018)Radiomics er konverteringen av digitale bilder til høydimensjonale data, og har oppstått på bakgrunn av konseptet om at medisinske bilder inneholder informasjon om en sykdom eller skade som kommer til syne ved bruk av ... -
Prediksjon av behandlingsutfall for hode- og halskreftpasienter ved bruk av radiomics og repetert elastisk nett teknikk
Fjellvang, Sofie (Master thesis, 2022)Radiomics er et fagområde som baserer seg på å hente ut egenskaper fra medisinske bilder ved hjelp av ulike dataalgoritmer. Disse egenskapene defineres ut i fra forholdet mellom nabovoksler, og skal avdekke mønstre og ... -
Preliminary evaluation of using machine learning to prioritise cancer patients for proton radiotherapy by predicting dose to organs at risk
Claesson, Linda Josephine (Master thesis, 2019)The investment in proton radiation therapy raises the question of how cancer patients should be prioritised for this treatment method. A large advantage to proton therapy is that one can minimise the radiation received ... -
Radiomics using MR brain scans and RENT for identifying patients receiving ADHD treatment
Mohammadi, Nasibeh (Master thesis, 2021)The core purpose of this thesis was to investigate whether the methylphenidate-based (MPH) treatment of male children patients having attention-deficit/hyperactivity disorder (ADHD) led to changes to five subcortical brain ... -
RENT—Repeated Elastic Net Technique for Feature Selection
Jenul, Anna Selina; Schrunner, Stefan; Liland, Kristian Hovde; Indahl, Ulf Geir; Futsæther, Cecilia Marie; Tomic, Oliver (Peer reviewed; Journal article, 2021) -
Searching for biomarkers of disease-free survival in head and neck cancers using PET/CT radiomics
Langberg, Geir Severin Rakh Elvatun (Master thesis, 2019)The goals of this thesis were to (1) study methodologies for radiomics data analysis, and (2) apply such methods to identify biomarkers of disease-free survival in head and neck cancers. Procedures for radiomics feature ... -
Segmentering av hode- og halskreft i PET/CT-bilder ved bruk av dype nevrale nettverk
Gjengedal, Malene Elise (Master thesis, 2021)Manuell segmentering av krefttumorer er en tidkrevende prosess som kan føre til stor inter- og intravariabilitet. Den lange inntegningstiden og usikkerheten i inntegningene, kan påvirke forløpet og utfallet av pasientens ... -
Semi-automatic tumor segmentation of rectal cancer based on functional magnetic resonance imaging
Knuth, Franziska Hanna; Grøndahl, Aurora Rosvoll; Winter, René; Torheim, Turid Katrine Gjerstad; Negård, Anne; Holmedal, Stein Harald; Bakke, Kine Mari; Meltzer, Sebastian; Futsæther, Cecilia Marie; Redalen, Kathrine (Peer reviewed; Journal article, 2022) -
Uncertainty quantification in automated tumor segmentation using deep learning
Abbas, Syed Ahmar (Master thesis, 2022)Introduction Head and neck cancer is one of the leading causes of cancer-related deaths globally and arguably has a long-standing history of impacting human life both medically and economically. Common treatment options ... -
Using machine learning and Repeated Elastic Net Technique for identification of biomarkers of early Alzheimer's disease
Olofsson, Charlott Kjærre (Master thesis, 2021)Alzheimer's disease is a neurodegenerative brain disease that damages neurons in the part of the brain involved in cognitive function, and early diagnosis is crucial for treatment that could slow down the progression of ... -
Utvikling av analyseprogram for identifikasjon av pulvermateriale basert på bildetekstur
Sogn, Linn Eirin; Smit, Anja Katarina (Master thesis, 2018)Kjernefysisk materiale som kommer på avveie skaper uro og bekymring grunnet assosiasjoner som gjerne kobles til anvendelse av slikt materiale, for eksempel knyttet til bruk i kjernefysiske våpen. Beslag av kjernefysisk ... -
Videreutvikling av et diagnostisk verktøy for automatisk svulstinntegning av livmorhalskreft i MR-bilder
Mühlbradt, Elise (Master thesis, 2016-08-17)Svulstavgrensning og svulstinntegning innenfor medisinsk avbildning er en utfordrende, tid-krevende og stadig mer kompleks del av strålebehandling. I denne oppgaven videreutvikles et program som automatiserer svulstinntegningen, ...