Abstract
Abstract Radiography images are widely utilized in the health sector to recognize the patient health condition. The noise and irrelevant region information minimize the entire disease detection accuracy and computation complexity. Therefore, in this study, statistical Kolmogorov–Smirnov test has been integrated with wavelet transform to overcome the de-noising issues. Then the cat swarm-optimized deep belief network is applied to extract the features from the affected region. The optimized deep learning model reduces the feature training cost and time and improves the overall disease detection accuracy. The network learning process is enhanced according to the AdaDelta learning process, which replaces the learning parameter with a delta value. This process minimizes the error rate while recognizing the disease. The efficiency of the system evaluated using image retrieval in medical application dataset. This process helps to determine the various diseases such as breast, lung, and pediatric studies.
Highlights
Radiography [1] is nothing but the imaging technique that utilizes the gamma, X-rays, and nonionizing and ionizing radiations to analyze and view the objects’ internal structure
The radiography process is widely applied in the medical sector in different formats [3,4] such as projectional radiography, computed tomography, dual-energy X-ray absorptiometry, contrast radiography, and fluoroscopy
This section examines the effectiveness of the cat swarm optimization algorithm-based deep belief network (CSA-DBN)-based radiographic image analysis process
Summary
Radiography [1] is nothing but the imaging technique that utilizes the gamma, X-rays, and nonionizing and ionizing radiations to analyze and view the objects’ internal structure. This radiographic process is widely applied in industrial and medical diagnostic purposes. The human body consists of various level substances with varying density information; nonionizing and ionizing radiations are utilized to capture the human organs [5,6]. This process is carried out by the radiographers, who are called the radiologists. The clinical analysis process requires the radiographic or medical imaging because the healthcare specialists access the patient’s organs, bones, blood vessels, and tissues via only the
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