Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?

Abstract

Objective: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. Materials and Methods: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. Results: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). Conclusion: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.

Intelligent recognition system of converter station operation text based on computer image acquisition

“…At the same time, Siqueira, G. and others think that because most of the equipments in converter stations are expensive, it is difficult for operators to find out the situation of equipment theft in time among many monitoring objects, which leads to equipment theft, thus causing troubles and huge economic losses. Therefore, it is urgent to develop a new intelligent video surveillance system [4] . Campos, G., et al said that the time consumption of image processing is closely related to the complexity of processing tasks.…”