Classification on normal chest x-ray and pneumonia x-ray

Qianwei Guo

doi:10.1117/12.2659294

22 November 2022 Classification on normal chest x-ray and pneumonia x-ray

Qianwei Guo

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 1247503 (2022) https://doi.org/10.1117/12.2659294
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

The usage of X-rays for classifying and diagnosing pneumonia has shown an excellent range of exactness and accuracy. This paper presents a binary-classification model that diagnoses patients who may have pneumonia by inputting their x-ray images and introduces the concepts used to develop that model. Keras and TensorFlow libraries are used in this analysis to produce a convolutional neural network model. The training data set which are used to train the model contains 5216 samples which represent 5216 different patients with either pneumonia x-ray image or normal x-ray image. The testing data set contains 624 samples which show how well the model generalizes on the new dataset. The model produces a classification accuracy of 75% on the testing set.

Citation Download Citation

Qianwei Guo "Classification on normal chest x-ray and pneumonia x-ray", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 1247503 (22 November 2022); https://doi.org/10.1117/12.2659294

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