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  • 1
    UID:
    almahu_BV046283282
    Format: 1 Online-Ressource (X, 147 Seiten) : , Illustrationen.
    ISBN: 978-981-150-798-4
    Series Statement: Lecture Notes in Bioengineering
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-150-797-7
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-150-799-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-150-800-4
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    gbv_1684976804
    Format: 1 Online-Ressource (X, 147 p. 64 illus., 61 illus. in color)
    Edition: 1st ed. 2019
    ISBN: 9789811507984
    Series Statement: Lecture Notes in Bioengineering
    Content: Chapter 1: Classification of Normal Versus Malignant Cells in B-ALL White Blood Cancer Microscopic Images -- Chapter 2: Classification of Leukemic B-Lymphoblast Cells from Blood Smear Microscopic Images with an Attention-Based Deep Learning Method and Advanced Augmentation Techniques -- Chapter 3
    Content: This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment
    Additional Edition: ISBN 9789811507977
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-15-0797-7
    Language: English
    URL: Cover
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  • 3
    UID:
    almafu_9959251694402883
    Format: 1 online resource (150 pages)
    Edition: 1st ed. 2019.
    ISBN: 981-15-0798-8
    Series Statement: Lecture Notes in Bioengineering,
    Content: This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment.
    Note: Chapter 1: Classification of Normal Versus Malignant Cells in B-ALL White Blood Cancer Microscopic Images -- Chapter 2: Classification of Leukemic B-Lymphoblast Cells from Blood Smear Microscopic Images with an Attention-Based Deep Learning Method and Advanced Augmentation Techniques -- Chapter 3: .
    Additional Edition: ISBN 981-15-0797-X
    Language: English
    Keywords: Llibres electrònics ; Llibres electrònics
    Library Location Call Number Volume/Issue/Year Availability
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