Mammogram denoising to improve the calcification detection performance of convolutional nets-Reference-Cited by-同舟云学术

Mammogram denoising to improve the calcification detection performance of convolutional nets

Published:2018-07-06 Issue: Volume: Page:
ISSN:
Container-title:14th International Workshop on Breast Imaging (IWBI 2018)
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Author:

Marrocco Claudio,Bria Alessandro,Di Sano Valerio,Borges Lucas R.,Savelli Benedetta,Molinara Mario,Mordang Jan-Jurre,Karssemeijer Nico,Tortorella Francesco

Publisher

SPIE

Reference33 articles.

1. American Cancer Society, “Cancer facts & figures 2017,” (2017).

2. Computer-aided detection and classification of microcalcifications in mammograms: a survey

3. A systematic review of computer-assisted diagnosis in diagnostic cancer imaging

4. A support vector machine approach for detection of microcalcifications

5. Relevance vector machine for automatic detection of clustered microcalcifications

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4. Combining Convolutional Neural Networks for Multi-context Microcalcification Detection in Mammograms;Computer Analysis of Images and Patterns;2019

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