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Visar resultat 1 - 5 av 40 avhandlingar som matchar ovanstående sökkriterier.

1. 1. Equivariant Neural Networks for Biomedical Image Analysis

   Författare :Karl Bengtsson Bernander; Ingela Nyström; Michal Kozubek; Uppsala universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computerized Image Processing; Datoriserad bildbehandling;

   Sammanfattning : While artificial intelligence and deep learning have revolutionized many fields in the last decade, one of the key drivers has been access to data. This is especially true in biomedical image analysis where expert annotated data is hard to come by. LÄS MER

3. 2. Neural networks in context: challenges and opportunities : a critical inquiry into prerequisites for user trust in decisions promoted by neural networks

   Författare :Lars Holmberg; Paul Davidsson; Per Linde; Carl Magnus Olsson; Maria Riveiro; Malmö universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Explainable AI; Machine Learning; Neural Network; Concept; Generalisation; Out-of-Distribution; Förklaringsbar AI; Maskininlärning; Neurala Nätverk; Koncept; Generalisering; Utanför-distributionen;

   Sammanfattning : Artificial intelligence and machine learning (ML) in particular increasingly impact human life by creating value from collected data. This assetisation affects all aspectsof human life, from choosing a significant other to recommending a product for us to consume. LÄS MER

4. 3. Water–fat separation in magnetic resonance imaging and its application in studies of brown adipose tissue

   Författare :Jonathan Andersson; Joel Kullberg; Håkan Ahlström; Mark Lubberink; Kerstin Lagerstrand; Uppsala universitet; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; brown adipose tissue; magnetic resonance imaging; water–fat signal separation; graph-cut; positron emission tomography; 18F-fludeoxyglucose; infrared thermography; machine learning; artificial neural networks; deep learning; convolutional neural networks; Radiology; Radiologi;

   Sammanfattning : Virtually all the magnetic resonance imaging (MRI) signal of a human originates from water and fat molecules. By utilizing the property chemical shift the signal can be separated, creating water- and fat-only images. LÄS MER

5. 4. Machine Learning Methods for Image Analysis in Medical Applications, from Alzheimer's Disease, Brain Tumors, to Assisted Living

   Författare :Chenjie Ge; Chalmers tekniska högskola; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; convolutional neural networks; Alzheimer s disease detection; machine learning; deep learning; fall detection; glioma subtype classification; generative adversarial networks; recurrent convolutional networks; spiking neural networks; visual prosthesis; semi-supervised learning;

   Sammanfattning : Healthcare has progressed greatly nowadays owing to technological advances, where machine learning plays an important role in processing and analyzing a large amount of medical data. This thesis investigates four healthcare-related issues (Alzheimer's disease detection, glioma classification, human fall detection, and obstacle avoidance in prosthetic vision), where the underlying methodologies are associated with machine learning and computer vision. LÄS MER

7. 5. Applications of Deep Learning in Medical Image Analysis : Grading of Prostate Cancer and Detection of Coronary Artery Disease

   Författare :Ida Arvidsson; Mathematical Imaging Group; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Medical Image Analysis; Deep Learning; Convolutional Neural Networks; Prostate Cancer; Gleason Grading; Coronary Artery Disease; Myocardial Perfusion Imaging;

   Sammanfattning : A wide range of medical examinations are using analysis of images from different types of equipment. Using artificial intelligence, the assessments could be done automatically. LÄS MER