scholarly journals A new automated method for the segmentation and characterization of breast masses on ultrasound images

2009 ◽  
Vol 36 (5) ◽  
pp. 1553-1565 ◽  
Author(s):  
Jing Cui ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Alexis Nees ◽  
Chintana Paramagul ◽  
...  
Keyword(s):  
Ultrasound Images ◽  
Breast Masses ◽  
Automated Method

scholarly journals Similarity evaluation in a content-based image retrieval (CBIR) CADx system for characterization of breast masses on ultrasound images

2011 ◽  
Vol 38 (4) ◽  
pp. 1820-1831 ◽  
Author(s):  
Hyun-chong Cho ◽  
Lubomir Hadjiiski ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Mark Helvie ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Ultrasound Images ◽  
Breast Masses

Computerized characterization of breast masses using three-dimensional ultrasound images

1998 ◽  
Author(s):  
Berkman Sahiner ◽  
Gerald L. LeCarpentier ◽  
Heang-Ping Chan ◽  
Marilyn A. Roubidoux ◽  
Nicholas Petrick ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Ultrasound Images ◽  
Breast Masses

Design and evaluation of a new automated method for the segmentation and characterization of masses on ultrasound images

2008 ◽  
Author(s):  
Jing Cui ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Alexis Nees ◽  
Chintana Paramagul ◽  
...  
Keyword(s):  
Ultrasound Images ◽  
Automated Method

Three-dimensional active contour model for characterization of solid breast masses on three-dimensional ultrasound images

2003 ◽  
Author(s):  
Berkman Sahiner ◽  
Aditya Ramachandran ◽  
Heang-Ping Chan ◽  
Marilyn A. Roubidoux ◽  
Lubomir M. Hadjiiski ◽  
...  
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Three Dimensional ◽  
Ultrasound Images ◽  
Breast Masses ◽  
Contour Model

Characterization of posterior acoustic features of breast masses on ultrasound images using artificial neural network

2008 ◽  
Author(s):  
Jing Cui ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Chintana Paramagul ◽  
Alexis Nees ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ultrasound Images ◽  
Acoustic Features ◽  
Breast Masses ◽  
Artificial Neural

Automated Characterization of Atheromatous Plaque in Intravascular Ultrasound Images Using Neuro Fuzzy Classifier

2012 ◽  
Vol 58 (4) ◽  
pp. 425-431 ◽  
Author(s):  
D. Selvathi ◽  
N. Emimal ◽  
Henry Selvaraj
Keyword(s):  
Intravascular Ultrasound ◽  
Human Error ◽  
Human Life ◽  
Classification Performance ◽  
Atheromatous Plaque ◽  
Ultrasound Images ◽  
Fuzzy Classifier ◽  
Neuro Fuzzy ◽  
Calcified Tissues

Abstract The medical imaging field has grown significantly in recent years and demands high accuracy since it deals with human life. The idea is to reduce human error as much as possible by assisting physicians and radiologists with some automatic techniques. The use of artificial intelligent techniques has shown great potential in this field. Hence, in this paper the neuro fuzzy classifier is applied for the automated characterization of atheromatous plaque to identify the fibrotic, lipidic and calcified tissues in Intravascular Ultrasound images (IVUS) which is designed using sixteen inputs, corresponds to sixteen pixels of instantaneous scanning matrix, one output that tells whether the pixel under consideration is Fibrotic, Lipidic, Calcified or Normal pixel. The classification performance was evaluated in terms of sensitivity, specificity and accuracy and the results confirmed that the proposed system has potential in detecting the respective plaque with the average accuracy of 98.9%.

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