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Review of Deep Learning Methods in Mammography, Cardiovascular and Microscopy Image Analysis - 2017

Review Of Deep Learning Methods In Mammography, Cardiovascular And Microscopy Image Analysis

Research Area:  Machine Learning

Abstract:

Computerized algorithms and solutions in processing and diagnosis mammography X-ray, cardiovascular CT/MRI scans, and microscopy image play an important role in disease detection and computer-aided decision-making. Machine learning techniques have powered many aspects in medical investigations and clinical practice. Recently, deep learning is emerging a leading machine learning tool in computer vision and begins attracting considerable attentions in medical imaging. In this chapter, we provide a snapshot of this fast growing field specifically for mammography, cardiovascular, and microscopy image analysis . We briefly explain the popular deep neural networks and summarize current deep learning achievements in various tasks such as detection, segmentation, and classification in these heterogeneous imaging modalities. In addition, we discuss the challenges and the potential future trends for ongoing work.

Keywords:  

Author(s) Name:  Gustavo Carneiro, Yefeng Zheng, Fuyong Xing & Lin Yang

Journal name:  Deep Learning and Convolutional Neural Networks for Medical Image Computing

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/978-3-319-42999-1_2

Volume Information:  pp 11–32