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- W4377704489 abstract "This research is aim to detect kidney cysts from human kidney Ultrasound (USG) 2D Images. This research uses data from Hospital patients as many as 25 Ultrasound images of the human kidney in the format image .jpg. This research uses the K-Nearest Neighbor (KNN) method for image classification of ultrasound images then using Gray Level Co-Occurrence Matrix (GLCM) method for image extraction to detect cyst and non-cyst regions from the result of classification after that using Artificial Neural Network (ANN) method type Backpropagation for image detection to find cysts from human kidney Ultrasound (USG) 2D Image from the result of image extraction. The result of this research is producing the algorithm to implement the method and the tool software application to detect kidney cysts from ultrasound 2D images. The accuracy of this tool is 84% which can detect with accurate 21 kidney cysts from 25 kidney ultrasound 2D images that validate of a Urology Specialist Doctor." @default.
- W4377704489 created "2023-05-24" @default.
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- W4377704489 date "2023-02-16" @default.
- W4377704489 modified "2023-10-17" @default.
- W4377704489 title "Detection of Kidney Cysts of Kidney Ultrasound Image using Hybrid Method: KNN, GLCM, and ANN Backpropagation" @default.
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- W4377704489 doi "https://doi.org/10.1109/iccosite57641.2023.10127703" @default.
- W4377704489 hasPublicationYear "2023" @default.
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