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Visar resultat 1 - 5 av 7 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Design, implementation and evaluation of a deep learning prototype to classify non-pigmented malignant skin cancer from dermatoscopic images

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Maria del Pilar Aguilera Manzanera; [2022]
    Nyckelord :Melanoma; Skin cancer; Dermatoscopy; Image classification; Machine learning; Artificial intelligence; Convolutional neural networks; Dermatology; Squamous cell carcinoma; Basal cell carcinoma; Actinic keratosis; Computer-aided Diagnostics; Digital dermatology; Technology and Engineering;

    Sammanfattning : The current trends for most fair-skinned populations are that the incidence of melanoma and non-pigmented skin lesions is growing, and this growing trend will continue for the upcoming years. The emergence of deep learning networks and their promising results in solving real-world healthcare problems and improving diagnostic accuracy opens new possibilities. LÄS MER

  3. 2. Identifying Chaos in Skin Lesions Using Deep Learning : A potential examination tool for dermatologists

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Marcus Odlander; [2021]
    Nyckelord :;

    Sammanfattning : This thesis investigated whether a deep learning model could learn features of Chaos,from the Chaos & Clues evaluation protocol, in a given dermatoscopic image data set. Asuccessful result could be of use in a future decision-support system for when dermatologists examine skin lesions for traces of melanoma (type of skin cancer). LÄS MER

  4. 3. 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

  5. 4. 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

  7. 5. 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