基于ALEXNET和混合ALEXNET- rf模型的CT图像肾结石检测

IF 0.9 4区工程技术 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Circuits Systems and Computers Pub Date : 2023-10-28 DOI:10.1142/s021812662450107x

M. Revathi, G. Raghuraman

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引用次数: 0

摘要

肾结石疾病是当今最常见的健康问题之一，需要重视早期诊断。几种成像方式用于检测肾结石。金标准CT扫描对肾结石的检测是有价值的。对于肾结石的检测，基于机器和深度学习的算法被广泛使用。为了提高早期技术的性能，开发了两种技术。首先，本文开发了一个基于alexnet的模型。利用随机森林(Random Forest, RF)增强的识别能力，我们开发了一个混合AlexNet-RF模型。两种模型都针对肾结石检测数据集进行了测试。该模型的性能证明，在准确率和损失方面，混合AlexNet-RF模型获得了可靠的较高检测率，约为97.1%至97.5%。这表明，在AlexNet的Softmax层中嵌入RF可以显著提高肾结石的预测率。

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Kidney Stone Detection from CT Images using ALEXNET and Hybrid ALEXNET-RF Models

Nowadays, kidney stone disease is one of the most common health issue which needs more attention for early diagnosis. Several imaging modalities are used for the detection of kidney stone. The gold standard CT scans are valuable for kidney stone detection. For kidney stone detection, machine and deep learning-based algorithms are widely used. In order to enhance the performance of earlier techniques, two techniques are developed. Initially, an AlexNet-based model is developed in this work. By using the enhanced recognition capability of Random Forest (RF), we developed a hybrid AlexNet-RF model. Both the models are tested against Kidney Stone Detection dataset. The performance of the proposed model proved that in terms of accuracy and loss the hybrid AlexNet-RF model secured reliable higher detection rate of approximately 97.1% to 97.5%. This showed that embedding RF in the Softmax layer of AlexNet significantly improves the prediction rate of kidney stone.

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来源期刊

Journal of Circuits Systems and Computers 工程技术-工程：电子与电气

CiteScore

2.80

自引率

26.70%

发文量

350

审稿时长

5.4 months

期刊介绍： Journal of Circuits, Systems, and Computers covers a wide scope, ranging from mathematical foundations to practical engineering design in the general areas of circuits, systems, and computers with focus on their circuit aspects. Although primary emphasis will be on research papers, survey, expository and tutorial papers are also welcome. The journal consists of two sections: Papers - Contributions in this section may be of a research or tutorial nature. Research papers must be original and must not duplicate descriptions or derivations available elsewhere. The author should limit paper length whenever this can be done without impairing quality. Letters - This section provides a vehicle for speedy publication of new results and information of current interest in circuits, systems, and computers. Focus will be directed to practical design- and applications-oriented contributions, but publication in this section will not be restricted to this material. These letters are to concentrate on reporting the results obtained, their significance and the conclusions, while including only the minimum of supporting details required to understand the contribution. Publication of a manuscript in this manner does not preclude a later publication with a fully developed version.