Mandayam, S. and Policar, R. Artificial neural networks. Lecture Note.

has been cited by the following article:

• TITLE: A new approach for classification of human brain CT images based on morphological operations

  AUTHORS: Ali Reza Fallahi, Mohammad Pooyan, Hassan Khotanlou

  KEYWORDS: CT Image; Feature Extraction; Classification; Morphological Operations; Automatic Diagnosis

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.3 No.1, January 12, 2010

  ABSTRACT: Automatic diagnosis may help to decrease human based diagnosis error and assist physicians to focus on the correct disease and its treatment and to avoid wasting time on diagnosis. In this paper computer aided diagnosis is applied to the brain CT image processing. We compared performance of morphological operations in extracting three types of features, i.e. gray scale, symmetry and texture. Some classifiers were applied to classify normal and abnormal brain CT images. It showed that morphological operations can improve the result of accuracy. Moreover SVM classifier showed better result than other classifiers.