Realizing PCB(Printed circuit board) defect detection is of great significance to promote the trend of PCB high-density, multi-layer as well as lightweight and thinning. To solve the problems of poor robustness, low accuracy rate, and excessive computation of current PCB defect detection methods, an improved YOLOv8n model named YOLOv8n-SM was proposed for PCB defect detection. The model adopts YOLOv8n as the benchmark model, replaces the SPPF (Spatial Pyramid Pooling-Fast) feature extraction module with SimSPPF(Simplified SPPF), and then replaces the CIoU(Complete Intersection over Union) loss function with the MPDIoU(Maximum Possible Distance Intersection over Union) loss function, to improve model detection accuracy. Validated on the PCB defect detection dataset, the improved PCB defect detection method based on YOLOv8n improves mAP0.5 by 0.7 and mAP0.5:0.95 by 0.6 compared to the original YOLOv8n algorithm. The experimental results shows that PCB defects detection model based on YOLOv8n-SM in the article better meets the requirements of practical applications for PCB defect detection.
Stage IA endometrial cancer is the only candidate for conservative management. Therefore, early diagnosis of endometrial cancer is very important. Co-registered photoacoustic (PA) and ultrasonic (US) imaging system is available to detect early endometrial cancer (EEC) based on a cylindrical diffuser. To correctly detect and diagnose EEC from FIGO stage IA and stage IB by co-registered PA and US imaging system, a convolutional neural network (CNN) classifier of EEC for co-registered PA and US images was proposed. Activation function ReLU and the dropout technique were used in the CNN classifier. The experiment results show the area under the receiver operating characteristic curve of the proposed algorithm is 0.9998 with a sensitivity of 98.75% and specificity of 98.75%. The CNN classifier could be used in the computer-aided diagnosis for early endometrial cancer of the co-registered PA and US imaging system.
Photoacoustic imaging is a promising technique that complements ultrasound and is able to distinguish benign from malignant tumors. Higher laser energy results in higher signal-to-noise ratio. Unfortunately, the higher laser energy is more costly and the maximum laser energy is also limited by the maximum permissible exposure imposed by the American National Standards Institute for human skin. The study of interaction of laser with tumorembedded uterine tissue is of great theoretical and practical significance for the laser diagnosis and treatment of endometrial cancer in medicine. In this paper, a 2D tumor-embedded uterine model, which was established by the histological structure of uterus, has been developed incorporating light propagation and heat transfer in soft tissues using a commercial FE simulation package, COMSOL Multiphysics. The light propagation were implemented through the tissues using the diffusion equation. Bioheat transfer in tissues was simulated using Pennes equation for temperature change, and the damage of the tissues was simulated by employing Arrhenius equation. The simulation results show that a cylindrical diffuser can illuminate almost the whole uterus at the same time. The light absorptions of the tumor and the normal tissue are big difference which could result in a high signal-to-noise ratio. Furthermore, the damage of the left side of the tumor is getting worse and irreversible after the laser irradiation. The conclusions are helpful to optimize the laser source and to improve the imaging depth in a photoacoustic imaging system, providing some significance for the further study of the early diagnosis of endometrial cancer.
Photoacoustic Imaging (PAI) has potential for clinical applications in real-time after a tiny modification of a current US scanner. The shared detector platform facilitates a natural integration of PA and US imaging creating a hybrid imaging technique that combines functional and structural information. In this work, two blood vessels phantom experiment was conducted by coregistered photoacoustic and ultrasonic imaging using clinical ultrasonic system. The vessels were placed about 6 cm away from the transducer. With conventional irradiation, real-time PA and US images could be obtained during the experiment. 450 of 2D PA and US images and reconstructed 3D imaging were taken by transducer scanning. The result indicates the system has the ability to get the PA signal in a deep tissue depth. 3D PA image clearly describes the tissue structure and benefits the detecting in clinical application.
Laser-induced thermotherapy (LITT) predicts the effects of laser applications in LITT and optimizes the efficacy of irradiation plans, the light distribution in liver tissue, the optical tissue properties, and the changes caused by thermal denaturation. In this paper, COMSOL Multiphysics, a commercially available Finite Element (FE) simulation software package, was used to simulate the interaction between laser and liver tissue. A short-pulse laser point source, coagulated liver tissue and uniform soft tissue submerged in water were established. In this study, two sets of simulation models were used to describe the principles: 1) Diffusion equation was used to simulate light propagation; 2) Temperature changes were simulated using biothermal equations. The experimental results show that there are significant differences in penetration depth and light energy distribution of native and coagulated liver tissues under laser irradiation with different wavelengths. The penetration depth of the liver tissue after heat coagulation is significantly reduced. In addition, the simulation can present the temperature curve during the clinical hyperthermia of liver cancer and determine the effect by various treatment parameters. These results provide a better understanding of laser-tissue interactions and may be helpful to researchers in the fields of laser medical.
Photoacoustic imaging (PAI) is a promising technique to image tumor angiogenesis development and detect endometrial carcinoma in earlier stages. The light absorption distribution of uterine tissue determines the imaging depth and range of PAI. In this work, a 3D triangular meshes tumor-embedded uterine optical model was established by the histological structure of uterus. The model is filled with strong scattering media (undiluted raw and homogenized milk, URHM) and air, respectively. Monte Carlo simulation is implemented based on the molecular optical simulation environment (MOSE) to find the absorption profiles of photons by transcervical laser illumination with cylindrically diffused light source (CDLS) or spherically diffused light source (SDLS) at wavelength 800nm. The results show the media with an extremely high scattering coefficient and an extremely low absorption coefficient like URHM helps the light propagations in a relatively small cavity. CDLS performs better when the tumor happens far from the light source center than the SDLS. On the same time, embedded tumors of the model filled with URHM are easier to detect by the transcervical laser illumination of CDLS than SDLS in the fundus of the uterus. The conclusions are helpful to optimize the laser source and to improve the imaging depth in a photoacoustic imaging system.
The Jones matrix and the Mueller matrix are main tools to study polarization devices. The Mueller matrix can also be used for biological tissue research to get complete tissue properties, while the commercial optical coherence tomography system does not give relevant analysis function. Based on the LabVIEW, a near real time display method of Mueller matrix image of biological tissue is developed and it gives the corresponding phase retardant image simultaneously. A quarter-wave plate was placed at 45 in the sample arm. Experimental results of the two orthogonal channels show that the phase retardance based on incident light vector fixed mode and the Mueller matrix based on incident light vector dynamic mode can provide an effective analysis method of the existing system.
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