Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging

المؤلفون المشاركون

Valvano, Gabriele
Santini, Gianmarco
Martini, Nicola
Ripoli, Andrea
Iacconi, Chiara
Chiappino, Dante
Della Latta, Daniele

المصدر

Journal of Healthcare Engineering

العدد

المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-9، 9ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2019-04-09

دولة النشر

مصر

عدد الصفحات

9

التخصصات الرئيسية

الصحة العامة
الطب البشري

الملخص EN

Cluster of microcalcifications can be an early sign of breast cancer.

In this paper, we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters.

In this work, we used 283 mammograms to train and validate our model, obtaining an accuracy of 99.99% on microcalcification detection and a false positive rate of 0.005%.

Our results show how deep learning could be an effective tool to effectively support radiologists during mammograms examination.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Valvano, Gabriele& Santini, Gianmarco& Martini, Nicola& Ripoli, Andrea& Iacconi, Chiara& Chiappino, Dante…[et al.]. 2019. Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging. Journal of Healthcare Engineering،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1175456

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Valvano, Gabriele…[et al.]. Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging. Journal of Healthcare Engineering No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1175456

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Valvano, Gabriele& Santini, Gianmarco& Martini, Nicola& Ripoli, Andrea& Iacconi, Chiara& Chiappino, Dante…[et al.]. Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging. Journal of Healthcare Engineering. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1175456

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1175456