@inproceedings{ba6e711143844030b414f59f2b2200b6,
title = "An automated Multispectral pixel and image classification system using texture analysis and neural networks",
abstract = "An automated pixel and image classification system has been developed to identify texture patterns within images after training with representative texture patterns. Multispectral analysis is applied to ultrasound images to form hyperspaces in which texture patterns are clustered. The clusters in the space are produced using run-length and Markovian texture statistics. Several neural network models can be selected to classify patterns. The system has been implemented in C on a Sun workstation in a window environment. It is highly automated and has potential for clinical applications. Texture patterns found in a series of cardiac ultrasound images of a tumor were used to train the system. The tumor was correcdy identified throughout a series of consecutive, closely-space tomographic images.",
author = "Yi Zheng and Foley, {David A.} and Kinter, {Thomas M.} and Greenleaf, {James F.}",
note = "Publisher Copyright: {\textcopyright} 1992 IEEE.; 1992 Ultrasonics Symposium ; Conference date: 20-10-1992 Through 23-10-1992",
year = "1992",
doi = "10.1109/ULTSYM.1992.276007",
language = "English (US)",
series = "Proceedings - IEEE Ultrasonics Symposium",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1093--1096",
booktitle = "1992 Ultrasonics Symposium Proceedings",
}