Abstract
In this study, it was aimed to perform cell detection in histopathologic images which contains ground truth information. Firstly, in the patches which taken from the image, it is aimed to find out whether there is a certain frequency content in certain directions by using Gabor Filter. Features are extracted from the patches. Thus, training and test data sets were created. Then, using the training data sets, k-nearest neighbors, support vector machine, and random forest trained classification methods were used for classification. The success of classifications were observed with using test dataset and the results were presented.
Keywords
Gabor filter
Artificial intelligence
Random forest
Computer science
Pattern recognition (psychology)
Support vector machine
Filter (signal processing)
Image (mathematics)
Computer vision
Ground truth
Subject Areas
AI in cancer detection
·Artificial Intelligence ·Physical Sciences
Digital Imaging for Blood Diseases
·Computer Vision and Pattern Recognition ·Physical Sciences
Biometric Identification and Security
·Signal Processing ·Physical Sciences
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