Model-free visualization of suspicious lesions in breast MRI based on supervised and unsupervised learning-Reference-Cited by-同舟云学术

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Model-free visualization of suspicious lesions in breast MRI based on supervised and unsupervised learning

Published:2008-03 Issue:2 Volume:21 Page:129-140
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Twellmann Thorsten,Meyer-Baese Anke,Lange Oliver,Foo Simon,Nattkemper Tim W.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference27 articles.

1. Feature extraction and classification of breast cancer on dynamic magnetic resonance imaging using artificial neural network;Abdolmaleki;Cancer Letters,2001

2. A fuzzy c-means (FCM)-based approach for computerized segmentation of breast lesions in dynamic contrast-enhanced MR images;Chen;Academic Radiology,2006

3. Dynamic magnetic resonance imaging of tumor perfusion;Collins;IEEE Engineering in Medicine and Biology Magazine,2004

4. An Introduction to Support Vector Machines and other Kernel-based Learning Methods;Cristiani,2000

5. Signal characteristics of malignant and benign lesions in dynamic 2D-MRI of the breast;Fischer;RoeFo,1993

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