Items related to An Optimal Multilevel Thresholding Based for Color...
Synopsis
Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable invasive cancer diagnosis solution. With minimum annotation information, the proposed method mines contrast patterns between normal and malignant images in unsupervised manner and generates a probability map of abnormalities to verify its reasoning. Particularly, a fully convolutional autoencoder is used to learn the dominant structural patterns among normal image patches. Patches that do not share the characteristics of this normal population are detected and analyzed by one-class support vector machine and 1-layer neural network. We apply the proposed method to a public breast cancer image set. Ourresults, in consultation with a senior pathologist, demonstrate that the proposed method outperforms existing methods. The obtained probability map could benefit the pathology practice by providing visualized verification data and potentially leads to a better understanding of data-driven diagnosis solutions.
"synopsis" may belong to another edition of this title.
Search results for An Optimal Multilevel Thresholding Based for Color...
Seller Image
An Optimal Multilevel Thresholding Based for Color Image Segmentation
Published by
LAP LAMBERT Academic Publishing Aug 2023, 2023
ISBN 10: 6206767590
ISBN 13: 9786206767596
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable invasive cancer diagnosis solution. With minimum annotation information, the proposed method mines contrast patterns between normal and malignant images in unsupervised manner and generates a probability map of abnormalities to verify its reasoning. Particularly, a fully convolutional autoencoder is used to learn the dominant structural patterns among normal image patches. Patches that do not share the characteristics of this normal population are detected and analyzed by one-class support vector machine and 1-layer neural network. We apply the proposed method to a public breast cancer image set. Ourresults, in consultation with a senior pathologist, demonstrate that the proposed method outperforms existing methods. The obtained probability map could benefit the pathology practice by providing visualized verification data and potentially leads to a better understanding of data-driven diagnosis solutions. 76 pp. Englisch. Seller Inventory # 9786206767596
Buy New
US$ 51.45
US$ 26.17 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 2 available
Seller Image
An Optimal Multilevel Thresholding Based for Color Image Segmentation
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206767590
ISBN 13: 9786206767596
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable invasive cancer diagnosis solution. With minimum annotation information, the proposed method mines contrast patterns between normal and malignant images in unsupervised manner and generates a probability map of abnormalities to verify its reasoning. Particularly, a fully convolutional autoencoder is used to learn the dominant structural patterns among normal image patches. Patches that do not share the characteristics of this normal population are detected and analyzed by one-class support vector machine and 1-layer neural network. We apply the proposed method to a public breast cancer image set. Ourresults, in consultation with a senior pathologist, demonstrate that the proposed method outperforms existing methods. The obtained probability map could benefit the pathology practice by providing visualized verification data and potentially leads to a better understanding of data-driven diagnosis solutions. Seller Inventory # 9786206767596
Buy New
US$ 54.88
US$ 39.82 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available
Seller Image
An Optimal Multilevel Thresholding Based for Color Image Segmentation
Published by
LAP Lambert Academic Publishing, 2023
ISBN 10: 6206767590
ISBN 13: 9786206767596
New
Softcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable inv. Seller Inventory # 1104277288
Buy New
US$ 43.64
US$ 55.74 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: Over 20 available
Seller Image
An Optimal Multilevel Thresholding Based for Color Image Segmentation
Published by
LAP LAMBERT Academic Publishing Aug 2023, 2023
ISBN 10: 6206767590
ISBN 13: 9786206767596
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable invasive cancer diagnosis solution. With minimum annotation information, the proposed method mines contrast patterns between normal and malignant images in unsupervised manner and generates a probability map of abnormalities to verify its reasoning. Particularly, a fully convolutional autoencoder is used to learn the dominant structural patterns among normal image patches. Patches that do not share the characteristics of this normal population are detected and analyzed by one-class support vector machine and 1-layer neural network. We apply the proposed method to a public breast cancer image set. Ourresults, in consultation with a senior pathologist, demonstrate that the proposed method outperforms existing methods. The obtained probability map could benefit the pathology practice by providing visualized verification data and potentially leads to a better understanding of data-driven diagnosis solutions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. Seller Inventory # 9786206767596
Buy New
US$ 51.45
US$ 68.27 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available
Seller Image
An Optimal Multilevel Thresholding Based for Color Image Segmentation
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206767590
ISBN 13: 9786206767596
New
Taschenbuch
Seller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. An Optimal Multilevel Thresholding Based for Color Image Segmentation | Gajanan Kale (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206767596 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 127637337
Buy New
US$ 46.23
US$ 79.65 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 5 available