Search for dissertations about: "Deep learning for diseases"

Showing result 1 - 5 of 17 swedish dissertations containing the words Deep learning for diseases.

  2. 1. Perspectives of Deep Learning for Neonatal Sepsis Detection

    Author : Antoine Honoré; Saikat Chatterjee; Eric Herlenius; Guy Carrault; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Neonatal Sepsis Detection; Normalizing Flows; Hidden Markov Models.; Djupinlärningsmodeller; Neonatal Sepsis detektion; Normaliserande Flöden; Dolda Markov modellerna.;

    Abstract : Newborns, whether born at term or preterm, are highly vulnerable and face life-threatening situations during their initial weeks of life every year. Even with hospitalization in a neonatal intensive care unit (NICU) and careful clinical monitoring, identifying infection-related incidents like sepsis is a challenging task. READ MORE

  4. 2. A path along deep learning for medical image analysis : With focus on burn wounds and brain tumors

    Author : Marco Domenico Cirillo; Anders Eklund; Veronika Cheplygina; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep learning; Medical image analysis; Burn wounds; Brain tumors; Image classification; Image segmentation; Image augmentation; CNNs; GANs;

    Abstract : The number of medical images that clinicians need to review on a daily basis has increased dramatically during the last decades. Since the number of clinicians has not increased as much, it is necessary to develop tools which can help doctors to work more efficiently. READ MORE

  5. 3. Automatic Melanoma Diagnosis in Dermoscopic Imaging Base on Deep Learning System

    Author : Yali Nie; Jan Lundgren; Mattias O'Nils; Claes Lundström; Mittuniversitetet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Melanoma classification; computer vision; Deep learning; CNN;

    Abstract : Melanoma is one of the deadliest forms of cancer. Unfortunately, its incidence rates have been increasing all over the world. One of the techniques used by dermatologists to diagnose melanomas is an imaging modality called dermoscopy. The skin lesion is inspected using a magnification device and a light source. READ MORE

  6. 4. Deriving biomarkers from computed tomography using deep learning

    Author : Meera Srikrishna; Göteborgs universitet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; CT; MRI; convoluted neural networks; deep learning; Dementia; Alzheimer s disease; Normal pressure hydrocephalus; brain segmentation;

    Abstract : X-ray computed tomography (CT) and magnetic resonance imaging (MRI) are widely used structural neuroimaging modalities. For brain atrophy assessment and volumetric quantification using automated methods, MRI is the preferred modality due to its superior soft tissue contrast. READ MORE

  7. 5. Methods for the analysis and characterization of brain morphology from MRI images

    Author : Irene Brusini; Chunliang Wang; Örjan Smedby; Eric Westman; Lars-Olof Wahlund; Jorge Cardoso; KTH; Karolinska Institutet; Karolinska Institutet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Brain MRI; Image Segmentation; Machine Learning; Deep Learning; Shape Analysis; Aging; Neurodegeneration; MRT av hjärnan; Bildsegmentering; Maskininlärning; Djupinlärning; Formanalys; Åldrande; Neurodegeneration; Medical Technology; Medicinsk teknologi;

    Abstract : Brain magnetic resonance imaging (MRI) is an imaging modality that produces detailed images of the brain without using any ionizing radiation. From a structural MRI scan, it is possible to extract morphological properties of different brain regions, such as their volume and shape. READ MORE