Speech enhancement methods based on microphone array adopt many microphones to record speech signal simultaneously. As spatial information is increased, these methods can increase speech recognition for cochlear implant in noisy environment. Due to the size limitation, the number of microphones used in the cochlear implant cannot be too large, which limits the design of microphone array beamforming. To balance the size limitation of cochlear implant and the spatial orientation information of the signal acquisition, we propose a speech enhancement and beamforming algorithm based on dual thin uni-directional / omni-directional microphone pairs (TP) in this paper. Each TP microphone contains two sound tubes for signal acquisition, which increase the overall spatial orientation information. In this paper, we discuss the beamforming characteristics with different gain vectors and the influence of the inter-microphone distance on beamforming, which provides valuable theoretical analysis and engineering parameters for the application of dual microphone speech enhancement technology in cochlear implants.
During the automatic reconstruction of panoramic images, the effect of dental arch curve fitting will affect the integrity of the content of the panoramic image. Metal implants in the patient’s mouth usually lead to a decrease in the contrast of the panoramic image, which affects the doctor’s diagnosis. In this paper, an automatic oral panoramic image reconstruction method was proposed. By calculating key image areas and image extraction fusion algorithms, the dental arch curve could be automatically detected and adjusted on a small number of images, and the intensity distribution of teeth, bone tissue and metal implants on the image could be adjusted to reduce the impact of metal on other tissues, to generate high-quality panoramic images. The method was tested on 50 cases of cone beam computed tomography (CBCT) data with good results, which can effectively improve the quality of panoramic images.
Effective medical image enhancement method can not only highlight the interested target and region, but also suppress the background and noise, thus improving the quality of the image and reducing the noise while keeping the original geometric structure, which contributes to easier diagnosis in disease based on the image enhanced. This article carries out research on strengthening methods of subtle structure in medical image nowadays, including images sharpening enhancement, rough sets and fuzzy sets, multi-scale geometrical analysis and differential operator. Finally, some commonly used quantitative evaluation criteria of image detail enhancement are given, and further research directions of fine structure enhancement of medical images are discussed.
Microphone array based methods are gradually applied in the front-end speech enhancement and speech recognition improvement for cochlear implant in recent years. By placing several microphones in different locations in space, this method can collect multi-channel signals containing a lot of spatial position and orientation information. Microphone array can also yield specific beamforming mode to enhance desired signal and suppress ambient noise, which is particularly suitable to be applied in face-to-face conversation for cochlear implant users. And its application value has attracted more and more attention from researchers. In this paper, we describe the principle of microphone array method, analyze the microphone array based speech enhancement technologies in present literature, and further present the technical difficulties and development trend.
Cognitive enhancement refers to the technology of enhancing or expanding the cognitive and emotional abilities of people without psychosis based on relevant knowledge of neurobiology. The common methods of cognitive enhancement include transcranial direct current stimulation (tDCS) and cognitive training (CT). tDCS takes effect quickly, with a short effective time, while CT takes longer to work, requiring several weeks of training, with a longer effective time. In recent years, some researchers have begun to use the method of tDCS combined with CT to regulate the cognitive function. This paper will sort out and summarize this topic from five aspects: perception, attention, working memory, decision-making and other cognitive abilities. Finally, the application prospect and challenges of technology are prospected.
In order to fully explore the neural oscillatory coupling characteristics of patients with mild cognitive impairment (MCI), this paper analyzed and compared the strength of the coupling characteristics for 28 MCI patients and 21 normal subjects under six different-frequency combinations. The results showed that the difference in the global phase synchronization index of cross-frequency coupling under δ-θ rhythm combination was statistically significant in the MCI group compared with the normal control group (P = 0.025, d = 0.398). To further validate this coupling feature, this paper proposed an optimized convolutional neural network model that incorporated a time-frequency data enhancement module and batch normalization layers to prevent overfitting while enhancing the robustness of the model. Based on this optimized model, with the phase locking value matrix of δ-θ rhythm combination as the single input feature, the diagnostic accuracy of MCI patients was (95.49 ± 4.15)%, sensitivity and specificity were (93.71 ± 7.21)% and (97.50 ± 5.34)%, respectively. The results showed that the characteristics of the phase locking value matrix under the combination of δ-θ rhythms can adequately reflect the cognitive status of MCI patients, which is helpful to assist the diagnosis of MCI.
In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.
Aiming at the problems of missing important features, inconspicuous details and unclear textures in the fusion of multimodal medical images, this paper proposes a method of computed tomography (CT) image and magnetic resonance imaging (MRI) image fusion using generative adversarial network (GAN) and convolutional neural network (CNN) under image enhancement. The generator aimed at high-frequency feature images and used double discriminators to target the fusion images after inverse transform; Then high-frequency feature images were fused by trained GAN model, and low-frequency feature images were fused by CNN pre-training model based on transfer learning. Experimental results showed that, compared with the current advanced fusion algorithm, the proposed method had more abundant texture details and clearer contour edge information in subjective representation. In the evaluation of objective indicators, QAB/F, information entropy (IE), spatial frequency (SF), structural similarity (SSIM), mutual information (MI) and visual information fidelity for fusion (VIFF) were 2.0%, 6.3%, 7.0%, 5.5%, 9.0% and 3.3% higher than the best test results, respectively. The fused image can be effectively applied to medical diagnosis to further improve the diagnostic efficiency.
Arthroscopic rotator cuff repair is widely used clinically, but the phenomenon of re-tear after repair is still common. Due to the special structure of the tendon-bone junction, the promotion of tissue regeneration from the perspective of biological enhancement has attracted attention. Platelet-rich plasma (PRP) is a supraphysiological concentration of autologous platelets, which can promote the healing of rotator cuff injury after repair. However, due to the lack of clinical use standards, not all PRPs are the same, there are clear differences between liquid PRP and solid platelet-rich fibrin, and many studies have not differentiated their properties. This article reviews the research progress of different types of PRP in the repair of rotator cuff injury, aiming to provide some reference for clinical treatment selection.
Objective To explore the differential diagnosis significance of 3.0T MRI united-sequences examination in the diagnosis of benign and malignant breast lesions. Methods A total of 67 breast lesions of 59 patients were collected prospectively, which be treated at the Sichuan Provincial People’s Hospital during July 2015 to January 2017. All patients were underwent bilateral breast 3.0T magnetic resonance plain scan, diffusion weighted imaging, and dynamic enhanced scan successively before surgical operation. Analysis of morphological features of the benign and malignant breast lesions, the time-signal intensity curve (TIC), the apparent diffusion coefficient (ADC), and the combination diagnosis of them were performed. Results Of all 59 patients, 67 lesions were confirmed by histopathology, including 18 benign lesions and 49 malignant lesions. The morphological features (including margin, shape, border, and evenness), the types of TIC of dynamic enhancement, and ADC value between the benign lesions and malignant lesions were statistically significant (P<0.05). The sensitivity and specificity of Fischer scoring system was 89.8% (44/49) and 61.1% (11/18) respectively. The sensitivity and specificity of TIC types was 83.7% (41/49) and 77.8% (14/18) respectively. The diagnostic threshold of ADC value was 1.012×10–3 mm2/s, with the sensitivity and specificity for the diagnosis was 91.8% (45/49) and 83.3% (15/18) respectively. The sensitivity and specificity of the combination of Fischer scoring system and TIC type for diagnosis between benign and malignant breast lesions was 95.9% (47/49) and 72.2% (13/18) respectively. The sensitivity and specificity of the combination of Fischer scoring system, TIC type, and ADC value for benign and malignant breast lesions was 98.0% (48/49) and 83.3% (15/18) respectively. Conclusion The combination of Fischer scoring system, TIC type, and diffusion-weighted imaging for the differential diagnosis between benign lesions and malignant lesions was more effective than single imaging method.