A Survey of Image Processing Algorithms in Digital Mammography-Reference-Cited by-同舟云学术

A Survey of Image Processing Algorithms in Digital Mammography

Published:2009 Issue: Volume: Page:631-657
ISSN:1860-949X
Container-title:Recent Advances in Multimedia Signal Processing and Communications
language:
Short-container-title:

Author:

Bozek Jelena,Mustra Mario,Delac Kresimir,Grgic Mislav

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-02900-4_24.pdf

Reference66 articles.

1. Acha, B., Rangayyan, R.M., Desautels, J.E.L.: : Detection of Microcalcifications in Mammograms. In: Suri, J.S., Rangayyan, R.M. (eds.) Recent Advances in Breast Imaging, Mammography, and Computer-Aided Diagnosis of Breast Cancer. SPIE, Bellingham (2006)

2. American College of Radiology (ACR): ACR Breast Imaging Reporting and Data System, Breast Imaging Atlas, 4th edn., Reston, VA, USA (2003)

3. Rangayyan, R.M., Ayres, F.J., Desautels, J.E.L.: A Review of Computer-Aided Diagnosis of Breast Cancer: Toward the Detection of Subtle Signs. Journal of the Franklin Institute 344(3-4), 312–348 (2007)

4. Sampat, M.P., Markey, M.K., Bovik, A.C.: Computer-Aided Detection and Diagnosis in Mammography. In: Bovik, A.C. (ed.) Handbook of Image and Video Processing. Elsevier Academic Press, Amsterdam (2005)

5. de Paredes, E.S.: Atlas of Mammography, 3rd edn. Lippincott Williams & Wilkins, Philadelphia (2007)

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transfer Driven Ensemble Learning Approach using ROI Pooling CNN For Enhanced Breast Cancer Diagnosis;Journal of Machine and Computing;2023-07-05

2. Classification of Breast Abnormalities Using Deep Learning;Journal of Communications Technology and Electronics;2022-12

3. A Hybrid Deep Transfer Learning of CNN-Based LR-PCA for Breast Lesion Diagnosis via Medical Breast Mammograms;Sensors;2022-06-30

4. BreastCNN: A Novel Layer-based Convolutional Neural Network for Breast Cancer Diagnosis in DMR-Thermogram Images;Applied Artificial Intelligence;2022-06-01

5. Comparative analysis of proficiencies of various textures and geometric features in breast mass classification using k-nearest neighbor;Visual Computing for Industry, Biomedicine, and Art;2022-01-12