Paper Info
Title
Enhancement of 3D modeling and classification of microcalcifications in breast computed tomography (BCT)
Abstract
Current computer aided diagnosis (CADx) software for digital mammography relies mainly on 2D techniques. With the emergence of three-dimensional (3D) breast imaging modalities such as breast Computed Tomography (BCT), there is an opportunity to analyze 3D features in the classification of calcifications. We previously reported our initial work on automated 3D feature detection and classification based on morphological descriptions for single microcalcifications within clusters [1]. In this work, we propose the expansion of the 3D classification methods to include novel microcalcification morphological feature detection such as including more morphological classes and replacing the 2D Radon transform by a 3D Radon transform. Results show that the classification rate improved compared to the previously reported results from a total of 546 to 559 consistently classified calcifications out of 635 total calcifications. This slight improvement is due to the use of the 3D Radon transform and incorporating methods to detect two classes not previously implemented. Future work will focus on adding feature detection and classification of cluster patterns.
Year
DOI
Venue
2014
10.1117/12.2043277
Proceedings of SPIE
Keywords
Field
DocType
Le Gal,Radon Transform,Support Vector Machine (SVM),Computer aided diagnosis (CADx)
Digital mammography,Computer vision,Microcalcification,Breast imaging,Computer-aided diagnosis,Artificial intelligence,Computed tomography,Classification rate,Radon transform,3D modeling,Physics
Conference
Volume
ISSN
Citations 
9034
0277-786X
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
hiam alquran100.34
Eman Shaheen212.51
j michael oconnor300.68
mufeed mahd400.34