Essays about: "Patient Volume Prediction"

Showing result 1 - 5 of 10 essays containing the words Patient Volume Prediction.

1. 1. Automatic Detection of Common Signal Quality Issues in MRI Data using Deep Neural Networks

   University essay from Linköpings universitet/Institutionen för medicinsk teknik

   Author : Erika Ax; Elin Djerf; [2023]
   Keywords : mr; magnetic resonance; machine learning; deep learning; anomaly detection; U-Net; autoencoder; 3D; classification; reconstruction; artefacts;

   Abstract : Magnetic resonance imaging (MRI) is a commonly used non-invasive imaging technique that provides high resolution images of soft tissue. One problem with MRI is that it is sensitive to signal quality issues. The issues can arise for various reasons, for example by metal located either inside or outside of the body. READ MORE

3. 2. Exploring Deep Learning Frameworks for Multiclass Segmentation of 4D Cardiac Computed Tomography

   University essay from Linköpings universitet/Institutionen för hälsa, medicin och vård

   Author : Norman Janurberg; Christian Luksitch; [2021]
   Keywords : Computed Tomography; Multiclass Segmentation; Image Segmentation; 4D; Deep Learning; MONAI; Unet; Cropping network; Multiaxis Segmentation;

   Abstract : By combining computed tomography data with computational fluid dynamics, the cardiac hemodynamics of a patient can be assessed for diagnosis and treatment of cardiac disease. The advantage of computed tomography over other medical imaging modalities is its capability of producing detailed high resolution images containing geometric measurements relevant to the simulation of cardiac blood flow. READ MORE

4. 3. Deep-learning based prediction model for dose distributions in lung cancer patients

   University essay from Stockholms universitet/Fysikum

   Author : Terese Hellström; [2021]
   Keywords : ;

   Abstract : 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. READ MORE

5. 4. Prediction of Dose Probability Distributions Using Mixture Density Networks

   University essay from KTH/Matematisk statistik

   Author : Viktor Nilsson; [2020]
   Keywords : Applied mathematics; machine learning; deep learning; mixture density network; dose planning; Tillämpad matematik; maskininlärning; djupinlärning; mixturdensitetsnätverk; dosplannerning;

   Abstract : In recent years, machine learning has become utilized in external radiation therapy treatment planning. This involves automatic generation of treatment plans based on CT-scans and other spatial information such as the location of tumors and organs. READ MORE

6. 5. Image Distance Learning for Probabilistic Dose–Volume Histogram and Spatial Dose Prediction in Radiation Therapy Treatment Planning

   University essay from KTH/Matematisk statistik

   Author : Ivar Eriksson; [2020]
   Keywords : Radiation therapy; automated planning; machine learning; autoencoder; distance optimisation; sparse pseudo-input Gaussian process; kernel density estimation; dose mimicking; dose–volume histogram; Strålbehandling; automatiserad dosplanering; maskininlärning; autoencoder; distansoptimering; glesa Gaussiska processer; sannolikhets-fördelnings-estimering; dosrekonstruktion; dos–volymhistogram;

   Abstract : Construction of radiotherapy treatments for cancer is a laborious and time consuming task. At the same time, when presented with a treatment plan, an oncologist can quickly judge whether or not it is suitable. This means that the problem of constructing these treatment plans is well suited for automation. READ MORE