Sökning: "Melanoma classification deep learning"

Hittade 5 uppsatser innehållade orden Melanoma classification deep learning.

  1. 1. Segmentation and Prediction of Mutation Status of Malignant Melanoma Whole-slide Images using Deep Learning

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Elin Johansson; Fanny Månefjord; [2021]
    Nyckelord :deep learning; image analysis; malignant melanoma; tissue segmentation; mutation classification; Inception v3; Technology and Engineering;

    Sammanfattning : Malignant melanoma is an aggressive type of skin cancer. Gene mutations can make the disease progress faster, but specialised treatment exists. Today, gene mutations are detected with DNA-analysis which is costly and time-consuming. LÄS MER

  2. 2. Malignant Melanoma Classification with Deep Learning

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Jakob Kisselgof; [2019]
    Nyckelord :Melanoma classification deep learning;

    Sammanfattning : Malignant melanoma is the deadliest form of skin cancer. If correctly diagnosed in time, the expected five-year survival rate can increase up to 97 %. Therefore, exploring various methods for early detection can contribute with tools which can be used to improve detection of disease and finally to make sure that help is given in time. LÄS MER

  3. 3. Deep Learning Method used in Skin Lesions Segmentation and Classification

    Master-uppsats, KTH/Medicinsk teknik

    Författare :Fengkai Wan; [2018]
    Nyckelord :Deep neural network; Skin lesion; Segmentation; Classification;

    Sammanfattning : Malignant melanoma (MM) is a type of skin cancer that is associated with a very poor prognosis and can often lead to death. Early detection is crucial in order to administer the right treatment successfully but currently requires the expertise of a dermatologist. LÄS MER

  4. 4. Evaluating a deep convolutional neural network for classification of skin cancer

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS); KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Joakim Boman; Alexander Volminger; [2018]
    Nyckelord :;

    Sammanfattning : Computer-aided diagnosis (CAD) has become an important part of themedical field. Skin cancer is a common and deadly disease that a CADsystem could potentially detect. It is clearly visible on the skin andtherefore only images of skin lesions could be used in order to pro-vide a diagnosis. LÄS MER

  5. 5. To be, or not to be Melanoma : Convolutional neural networks in skin lesion classification

    Master-uppsats, KTH/Medicinsk teknik

    Författare :Andreas Nylund; [2016]
    Nyckelord :Clinical Decision Support; Convolutional Neural Networks; Deep Learning; Dermoscopy; Machine Learning; Melanoma;

    Sammanfattning : Machine learning methods provide an opportunity to improve the classification of skin lesions and the early diagnosis of melanoma by providing decision support for general practitioners. So far most studies have been looking at the creation of features that best indicate melanoma. LÄS MER