Image analysis – Applications – Biomedical applications
Reexamination Certificate
2011-01-25
2011-01-25
Tabatabai, Abolfazl (Department: 2624)
Image analysis
Applications
Biomedical applications
C382S224000, C600S300000
Reexamination Certificate
active
07876943
ABSTRACT:
According to an aspect of the invention, a method for training a classifier for classifying candidate regions in computer aided diagnosis of digital medical images includes providing a training set of annotated images, each image including one or more candidate regions that have been identified as suspicious, deriving a set of descriptive feature vectors, where each candidate region is associated with a feature vector. A subset of the features are conditionally dependent, and the remaining features are conditionally independent. The conditionally independent features are used to train a naïve Bayes classifier that classifies the candidate regions as lesion or non-lesion. A joint probability distribution that models the conditionally dependent features, and a prior-odds probability ratio of a candidate region being associated with a lesion are determined from the training images. A new classifier is formed from the naïve Bayes classifier, the joint probability distribution, and the prior-odds probability ratio.
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International Search Report including Notification of Transmittal of the International Search Report, International Search Report, and Written Opinion of the International Searching Authority.
Dewan Maneesh
Jerebko Anna
Salganicoff Marcos
Steck Harald
Siemens Medical Solutions USA , Inc.
Tabatabai Abolfazl
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