In this paper a new technique, Empirical Mode Decomposition(EMD), for use in non-stationary and non-linear data processing, was introduced. Some simulated signal, real ECG and RRI signals combined with Hilbert Transform method were analyzed. The authors also put emphasis on the differences between EMD and Wavelet Transform.
Algorithms ; Computer Simulation ; Diagnosis, Computer-Assisted ; methods ; Electrocardiography ; Heart Rate

Recently, artificial intelligence (AI) has been widely applied in the diagnosis and treatment of urinary diseases with the development of data storage, image processing, pattern recognition and machine learning technologies. Based on the massive biomedical big data of imaging and histopathology, many urinary system diseases (such as urinary tumor, urological calculi, urinary infection, voiding dysfunction and erectile dysfunction) will be diagnosed more accurately and will be treated more individualizedly. However, most of the current AI diagnosis and treatment are in the pre-clinical research stage, and there are still some difficulties in the wide application of AI. This review mainly summarizes the recent advances of AI in the diagnosis of prostate cancer, bladder cancer, kidney cancer, urological calculi, frequent micturition and erectile dysfunction, and discusses the future potential and existing problems.
Artificial Intelligence ; trends ; Diagnosis, Computer-Assisted ; trends ; Humans ; Image Processing, Computer-Assisted ; Urologic Diseases ; diagnosis

In the paper, iridology and computer-aided iridiagnosis technologies are briefly introduced and the extraction method of the collarette contour is then investigated. The iris map can be overlapped on the original iris image based on collarette contour extraction. The research on collarette contour extraction and iris map overlap is of great importance to computer-aided iridiagnosis technologies.
Diagnosis, Computer-Assisted ; methods ; Humans ; Image Processing, Computer-Assisted ; methods ; Iris Diseases ; diagnosis ; Software

In dentistry, RadioVisioGraphy was introduced as a first electronic dental x-ray imaging modality in 1989. Thereafter, many types of direct digital radiographic systems have been produced in the last decade. They are based either on charge-coupled device(CCD) or on storage phosphor technology. In addition, new types of digital radiographic system using amorphous selenium, image intensifier etc. are under development. Advantages of digital radiographic system are elimination of chemical processing, reduction in radiation dose, image processing, computer storage, electronic transfer of images and so on. Image processing includes image enhancement, image reconstruction, digital subtraction, etc. Especially digital subtraction and reconstruction can be applied in many aspects of clinical practice and research. Electronic transfer of images enables filmless dental hospital and teleradiology/teledentistry system. Since the first image management and communications system(IMACS) for dentomaxillofacial radiology was reported in 1992, IMACS in dental hospital has been increasing. Meanwhile, researches about computer-assisted diagnosis, such as structural analysis of bone trabecular patterns of mandible, feature extraction, automated identification of normal landmarks on cephalometric radiograph and automated image analysis for caries or periodontitis, have been performed actively in the last decade. Further developments in digital radiographic imaging modalities, image transmission system, imaging processing and automated analysis software will change the traditional clinical dental practice in the 21st century.
Chemical Processes ; Dentistry* ; Diagnosis, Computer-Assisted ; Image Enhancement ; Image Processing, Computer-Assisted ; Mandible ; Periodontitis ; Selenium

The biochemical analysis of urine is an important inspection and diagnosis method in hospitals. The conventional method of urine analysis covers mainly colorimetric visual appraisement and automation detection, in which the colorimetric visual appraisement technique has been superseded basically, and the automation detection method is adopted in hospital; moreover, the price of urine biochemical analyzer on market is around twenty thousand RMB yuan (Y), which is hard to enter into ordinary families. It is known that computer vision system is not subject to the physiological and psychological influence of person, its appraisement standard is objective and steady. Therefore, according to the color theory, we have established a computer vision system, which can carry through collection, management, display, and appraisement of color difference between the color of standard threshold value and the color of urine test paper after reaction with urine liquid, and then the level of an illness can be judged accurately. In this paper, we introduce the Urine Test Biochemical Analysis method, which is new and can be popularized in families. Experimental result shows that this test method is easy-to-use and cost-effective. It can realize the monitoring of a whole course and can find extensive applications.
Automation ; Colorimetry ; methods ; Diagnosis, Computer-Assisted ; Humans ; Signal Processing, Computer-Assisted ; Urinalysis ; methods

Precise segmentation of lung field is a crucial step in chest radiographic computer-aided diagnosis system. With the development of deep learning, fully convolutional network based models for lung field segmentation have achieved great effect but are poor at accurate identification of the boundary and preserving lung field consistency. To solve this problem, this paper proposed a lung segmentation algorithm based on non-local attention and multi-task learning. Firstly, an encoder-decoder convolutional network based on residual connection was used to extract multi-scale context and predict the boundary of lung. Secondly, a non-local attention mechanism to capture the long-range dependencies between pixels in the boundary regions and global context was proposed to enrich feature of inconsistent region. Thirdly, a multi-task learning to predict lung field based on the enriched feature was conducted. Finally, experiments to evaluate this algorithm were performed on JSRT and Montgomery dataset. The maximum improvement of Dice coefficient and accuracy were 1.99% and 2.27%, respectively, comparing with other representative algorithms. Results show that by enhancing the attention of boundary, this algorithm can improve the accuracy and reduce false segmentation.
X-Rays ; Algorithms ; Diagnosis, Computer-Assisted ; Thorax/diagnostic imaging* ; Lung/diagnostic imaging* ; Image Processing, Computer-Assisted

Coronary angiography (CAG) as a typical imaging modality for the diagnosis of coronary diseases hasbeen widely employed in clinical practices. For CAG-based computer-aided diagnosis systems, accurate vessel segmentation plays a fundamental role. However, patients with bradycardia usually have a pacemaker which frequently interferes the vessel segmentation. In this case, the segmentation of vessels will be hard. To mitigate interferences of pacemakers and then extract main vessels more effectively in CAG images, we propose an approach. At first, a pseudo CAG (pCAG) image is generated through a part of a CAG sequence, in which the pacemaker exists. Then, a local feature descriptor is employed to register the relative location of pacemaker between the pCAG image and the target CAG image. Finally, combining the registration result and segmentation results of main vessels and pacemaker, interferences of pacemaker are removed and the segmentation of main vessels is improved. The proposed method is evaluated based on 11 CAG images with pacemakers acquired in clinical practices. An optimization ratio of the Dice coefficient is 12.04%, which demonstrates that our method can remove overlapping pacemakers and achieve the improvement of main vessel segmentation in CAG images.Our method can further become a helpful component in a CAG-based computer-aided diagnosis system, improving its diagnosis accuracy and efficiency.
Humans ; Coronary Angiography/methods* ; Diagnosis, Computer-Assisted ; Pacemaker, Artificial ; Image Processing, Computer-Assisted/methods* ; Algorithms

This paper, analyzes the defects and its limitations of computer-aided diagnosis system (CADS) in clinical practice in the past, proposes a new pattern CADS of designing method. We used the theory of multidetection, stored the accumulated experience in computer, established the knowledge base, and made the medical diagnosis through maximizing a posteriori (MAP) judgement rule. Statistical data revealed that the CADS had a high accuracy rate. The medical diagnosis can meet the demand for clinical treatments, and realize the clinical diagnostic application of information technology.
Bayes Theorem ; Decision Making, Computer-Assisted ; Diagnosis, Computer-Assisted ; methods ; Humans

In this paper, a new method of contour analysis is presented to find path in endoscopy navigation. At first, edge detection is used to endoscope image. Then we do skeleton extraction and connect the edge skeleton to contours by grouping criteria. At last we can get navigation information by analyzing the contours. Experiments show that this algorithm has good precision and stability.
Algorithms ; Diagnosis, Computer-Assisted ; Endoscopy ; methods ; Gastroscopy ; Humans ; Image Enhancement ; methods ; Image Processing, Computer-Assisted

Using the common algorithm and the Mellin algorithm of a continuous wavelet transform, we analyzed the pulse signals of 15 heroin addicts and 15 normal persons. With the use of two algorithms, every pulse signal was processed under 4 scales. From the analyzed results, we found that there was significant difference of wavelet transform coefficients in the time interval 0.2 to approximately 0.4 seconds between the heroin addicts and normal persons. In this paper, the critical parameter used to classify heroin addicts and normal persons is given to every algorithm. The research result of this paper shows that the continuous wavelet transform is really an effective method for processing pulse signals.
Algorithms ; Diagnosis, Computer-Assisted ; Heroin Dependence ; physiopathology ; Humans ; Medicine, Chinese Traditional ; Pulse ; Signal Processing, Computer-Assisted