Objective To develop an innovative recognition algorithm that aids physicians in the identification of pulmonary nodules. MethodsPatients with pulmonary nodules who underwent thoracoscopic surgery at the Department of Thoracic Surgery, Affiliated Drum Tower Hospital of Nanjing University Medical School in December 2023, were enrolled in the study. Chest surface exploration data were collected at a rate of 60 frames per second and a resolution of 1 920×1 080. Frame images were saved at regular intervals for subsequent block processing. An algorithm database for lung nodule recognition was developed using the collected data. ResultsA total of 16 patients were enrolled, including 9 males and 7 females, with an average age of (54.9±14.9) years. In the optimized multi-topology convolutional network model, the test results demonstrated an accuracy rate of 94.39% for recognition tasks. Furthermore, the integration of micro-variation amplification technology into the convolutional network model enhanced the accuracy of lung nodule identification to 96.90%. A comprehensive evaluation of the performance of these two models yielded an overall recognition accuracy of 95.59%. Based on these findings, we conclude that the proposed network model is well-suited for the task of lung nodule recognition, with the convolutional network incorporating micro-variation amplification technology exhibiting superior accuracy. Conclusion Compared to traditional methods, our proposed technique significantly enhances the accuracy of lung nodule identification and localization, aiding surgeons in locating lung nodules during thoracoscopic surgery.
The method for detecting the negative terms in Chinese electronic medical record (EMR) is useful in providing evidence for constructing concept index. In this respect, we adopted an improved method which combined maximum matching with mutual information in order to extract terms in EMRs. This method can overcome the influence of overlay ambiguity. In addition, for the determination of negative semantic, we also adopted an improved method which combined rule-based method with word co-occurrence. This new method can reduce the probability of appearance of false positive terms caused by punctuation input errors. The result showed that the negative predictive value is 7.85% higher than the rule-based method.
Clinical studies had demonstrated that early diagnosis of lesion could significantly reduce the risk of cancer. Magneto-acoustic-electrical tomography (MAET) is expected to become a new detection method due to its advantages of high resolution and high contrast. Based on thinking of modular design, a low-cost, digital magneto-acoustic conductivity detection system was designed and implemented in this study. The theory of MAET using chirp continuous wave excitation was introduced. The results of homogeneous phantom experiment with 0.5% NaCl clearly showed that the conductivity curve of homogeneous phantom was highly consistent with the actual physical size, which indicated that the chirp excitation theory in our proposed system was correct and feasible. Besides, the resolution obtained by 1 000 μs sweep time was better than that obtained by 500 μs and 1 500 μs, which means that sweep time is an important factor affecting the detection resolution of the conductivity. The same result was obtained in the experiments carried out on homogeneous phantoms with different concentrations of NaCl, which demonstrated the repeatability of our proposed MAET system.
The dynamic electrocardiogram (ECG) collected by wearable devices is often corrupted by motion interference due to human activities. The frequency of the interference and the frequency of the ECG signal overlap with each other, which distorts and deforms the ECG signal, and then affects the accuracy of heart rate detection. In this paper, a heart rate detection method that using coarse graining technique was proposed. First, the ECG signal was preprocessed to remove the baseline drift and the high-frequency interference. Second, the motion-related high amplitude interference exceeding the preset threshold was suppressed by signal compression method. Third, the signal was coarse-grained by adaptive peak dilation and waveform reconstruction. Heart rate was calculated based on the frequency spectrum obtained from fast Fourier transformation. The performance of the method was compared with a wavelet transform based QRS feature extraction algorithm using ECG collected from 30 volunteers at rest and in different motion states. The results showed that the correlation coefficient between the calculated heart rate and the standard heart rate was 0.999, which was higher than the result of the wavelet transform method (r = 0.971). The accuracy of the proposed method was significantly higher than the wavelet transform method in all states, including resting (99.95% vs. 99.14%, P < 0.01), walking (100% vs. 97.26%, P < 0.01) and running (100% vs. 90.89%, P < 0.01). The absolute error [0 (0, 1) vs. 1 (0, 1), P < 0.05] and relative error [0 (0, 0.59) vs. 0.52 (0, 0.72), P < 0.05] of the proposed method were significantly lower than the wavelet transform method during running state. The method presented in this paper shows high accuracy and strong anti-interference ability, and is potentially used in wearable devices to realize real-time continuous heart rate monitoring in daily activities and exercise conditions.
This paper performs a comprehensive study on the computer-aided detection for the medical diagnosis with deep learning. Based on the region convolution neural network and the prior knowledge of target, this algorithm uses the region proposal network, the region of interest pooling strategy, introduces the multi-task loss function: classification loss, bounding box localization loss and object rotation loss, and optimizes it by end-to-end. For medical image it locates the target automatically, and provides the localization result for the next stage task of segmentation. For the detection of left ventricular in echocardiography, proposed additional landmarks such as mitral annulus, endocardial pad and apical position, were used to estimate the left ventricular posture effectively. In order to verify the robustness and effectiveness of the algorithm, the experimental data of ultrasonic and nuclear magnetic resonance images are selected. Experimental results show that the algorithm is fast, accurate and effective.
Objective To explore the methods of early diagnosis of arteriosclerosis obliterans of lower extremity (ASOLE). Methods The related literatures on ASOLE detection means adopted clinically were reviewed, and their advantages and disadvantages were compared.Results Asymptomatic ASOLE could be discovered by determination of ankle brachial index (ABI) and toe brachial index (TBI), which was a good index for arterial function assessment of lower extremity. Pulse wave velocity (PWV) was more vulnerable and less sensitive than ABI, and therefore more suitable for screening of a large sample. ASI was an index to assess arterial structure and function, and it had a good correlation with PWV. Flow-mediated dilation (FMD) was a measurement evaluating the function of endothelial cell; Pulse wave measurement was simple, sensitive, and its result was reliable. Color Doppler ultrasonography could localizate the lesion and determine the degree of stenosis at the same time. Multiple-slice CT angiography (MSCTA) was more accurate than color Doppler ultrasonography, but its inherent shortcomings, such as nephrotoxicity of contrast agent, was still need to be resolved. 3D-contrast enhancement magnetic resonance angiography (CEMRA) had little nephrotoxicity, but a combination of other imaging methods was necessary. Microcirculation detections required high consistency of the measurement environment, but they were simple, sensitive and noninvasive, and therefore could be used for screening of ASO. Conclusion Publicity and education of highrisk groups, and reasonable selection of all kinds of detection means, are helpful to improve the early diagnosis of ASOLE.
In order to study the effect of light with different wavelengths on the motion behavior of carp robots, phototaxis experiment, anatomical experiment, light control experiment and speed measurement experiment were carried out in this study. Blue, green, yellow and red light with different wavelength were used to conduct phototaxis experiments on carp to observe their movement behavior. By dissecting the skull bones of the carp to determine the appropriate location to carry the light control device, we independently developed a light control carrying device which was suitable for any illumination intensity environment. The experiment of the light-controlled carp robots was carried out. The motion behavior of the carp robot was checked by using computer binocular stereo vision technology. The motion trajectory of the carp robot was tracked and obtained by applying kernel correlation filter (KCF) algorithm. The motion velocity of the carp robot at different wavelengths was calculated according to their motion trajectory. The results showed that carps’ sensitivity to different light changed from strong to weak in the order of blue, red, yellow and green, so that using light with different wavelengths to control the speed of the carp robot has certain laws to follow. A new method to avoid brain damage in carp robots control can be provided in this study.
Computer-aided detection (CAD) of pulmonary nodule technology can effectively assist the radiologist to enhance lung nodule detection efficiency and accuracy rate, so it can lay the foundation for the early diagnosis of lung cancer. In order to provide reference for the scholars and to develop the CAD technology, we in this paper review the technology research and development of CAD of the pulmonary nodules which is based on CT image in recent years both home and abroad. At the same time, we also analyse the advantages and shortcomings of different methods. Then we present the improvement direction for reference. According to the literature in recent years, there still has been large development space in CAD technology for pulmonary nodules. The establishment and improvement of the CAD system in each step would be of great scientific value.
Objective To evaluate the possibility of detection mutations of 〖JP2〗multiple genes in stool for secondary screening for colorectal cancer. Methods Tumor specimens and stool samples from 40 patients with colorectal cancer and 40 normal persons were examined for mutations of p53, K-ras and APC gene by polymerase chain reaction single strand conformation polymorphism (PCR-SSCP) and silver nitrate staining. Results ①The mutation rate of p53, K-ras and APC gene in the tissues and stools of colorectal cancer respectively were 57.50%, 50.00%, 60.00% and 42.86%, 40.00%, 51.43%, and no mutations were found in normal mucosa and stool. ②The mutation ratioes between multiple gene and single gene had significant difference (P＜0.05). ③The sensitivities had no significant difference between faecal occult blood test (FOBT) and multiple gene mutations detection in the diagnosis of colorectal cancer, but the specificity of the latter was higher than FOBT (P＜0.05). Conclusion Detection of multiple gene mutations in stool is a vauble method in the secondary screening for colorectal cancer.
Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.