Iterative, Deep Synthetic Aperture Sonar Image Segmentation

Synthetic aperture sonar (SAS) systems produce high-resolution images of the seabed environment. Moreover, deep learning has demonstrated superior ability in finding robust features for automating imagery analysis. However, the success of deep learning is conditioned on having lots of labeled training data, but obtaining generous pixel-level annotations of SAS imagery is often practically infeasible. This challenge has thus far limited the adoption of deep learning methods for SAS segmentation. Algorithms exist to segment SAS imagery in an unsupervised manner, but they lack the benefit of state-of-the-art learning methods and the results present significant room for improvement. In view of the above, we propose a new iterative algorithm for unsupervised SAS image segmentation combining superpixel formation, deep learning, and traditional clustering methods. We call our method Iterative Deep Unsupervised Segmentation (IDUS). IDUS is an unsupervised learning framework that can be divided into four main steps: 1) A deep network estimates class assignments. 2) Low-level image features from the deep network are clustered into superpixels. 3) Superpixels are clustered into class assignments (which we call pseudo-labels) using $k$-means. 4) Resulting pseudo-labels are used for loss backpropagation of the deep network prediction. These four steps are performed iteratively until convergence. A comparison of IDUS to current state-of-the-art methods on a realistic benchmark dataset for SAS image segmentation demonstrates the benefits of our proposal even as the IDUS incurs a much lower computational burden during inference (actual labeling of a test image). Finally, we also develop a semi-supervised (SS) extension of IDUS called IDSS and demonstrate experimentally that it can further enhance performance while outperforming supervised alternatives that exploit the same labeled training imagery.Comment: arXiv admin note: text overlap with arXiv:2107.1456

Dynamic region of interest transcoding for multipoint video conferencing

This paper presents a region of interest transcoding scheme for multipoint video conferencing to enhance the visual quality. In a multipoint videoconference, usually there are only one or two active conferees at one time which are the regions of interest to the other conferees involved. We propose a Dynamic Sub-Window Skipping (DSWS) scheme to firstly identify the active participants from the multiple incoming encoded video streams by calculating the motion activity of each sub-window, and secondly reduce the frame-rates of the motion inactive participants by skipping these less-important subwindows. The bits saved by the skipping operation are reallocated to the active sub-windows to enhance the regions of interest. We also propose a low-complexity scheme to compose and trace the unavailable motion vectors with a good accuracy in the dropped inactive sub-windows after performing the DSWS. Simulation results show that the proposed methods not only significantly improve the visual quality on the active subwindows without introducing serious visual quality degradation in the inactive ones, but also reduce the computational complexity and avoid whole-frame skipping. Moreover, the proposed algorithm is fully compatible with the H.263 video coding standard. 1

Power Allocation and Time-Domain Artificial Noise Design for Wiretap OFDM with Discrete Inputs

Optimal power allocation for orthogonal frequency division multiplexing (OFDM) wiretap channels with Gaussian channel inputs has already been studied in some previous works from an information theoretical viewpoint. However, these results are not sufficient for practical system design. One reason is that discrete channel inputs, such as quadrature amplitude modulation (QAM) signals, instead of Gaussian channel inputs, are deployed in current practical wireless systems to maintain moderate peak transmission power and receiver complexity. In this paper, we investigate the power allocation and artificial noise design for OFDM wiretap channels with discrete channel inputs. We first prove that the secrecy rate function for discrete channel inputs is nonconcave with respect to the transmission power. To resolve the corresponding nonconvex secrecy rate maximization problem, we develop a low-complexity power allocation algorithm, which yields a duality gap diminishing in the order of O(1/\sqrt{N}), where N is the number of subcarriers of OFDM. We then show that independent frequency-domain artificial noise cannot improve the secrecy rate of single-antenna wiretap channels. Towards this end, we propose a novel time-domain artificial noise design which exploits temporal degrees of freedom provided by the cyclic prefix of OFDM systems {to jam the eavesdropper and boost the secrecy rate even with a single antenna at the transmitter}. Numerical results are provided to illustrate the performance of the proposed design schemes.Comment: 12 pages, 7 figures, accepted by IEEE Transactions on Wireless Communications, Jan. 201

Integrin-mediated membrane blebbing is dependent on the NHE1 and NCX1 activities.

Integrin-mediated signal transduction and membrane blebbing have been well studied to modulate cell adhesion, spreading and migration^1-6^. However, the relationship between membrane blebbing and integrin signaling has not been explored. Here we show that integrin-ligand interaction induces membrane blebbing and membrane permeability change. We found that sodium-proton exchanger 1 (NHE1) and sodium-calcium exchanger 1 (NCX1) are located in the membrane blebbing sites and inhibition of NHE1 disrupts membrane blebbing and decreases membrane permeability change. However, inhibition of NCX1 enhances cell blebbing to cause cell swelling which is correlated with an intracellular sodium accumulation induced by NHE17. These data suggest that sodium influx induced by NHE1 is a driving force for membrane blebbing growth, while sodium efflux induced by NCX1 in a reverse mode causes membrane blebbing retraction. Together, these data reveal a novel function of NHE1 and NCX1 in membrane permeability change and blebbing and provide the link for integrin signaling and membrane blebbing

Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis

BACKGROUND: The treatment of trigger finger so far has heavily relied on clinicians’ evaluations for the severity of patients’ symptoms and the functionality of affected fingers. However, there is still a lack of pathological evidence supporting the criteria of clinical evaluations. This study’s aim was to correlate clinical classification and pathological changes for trigger finger based on the tissue abnormality observed from microscopic images. METHODS: Tissue samples were acquired, and microscopic images were randomly selected and then graded by three pathologists and two physicians, respectively. Moreover, the acquired images were automatically analyzed to derive two quantitative parameters, the size ratio of the abnormal tissue region and the number ratio of the abnormal nuclei, which can reflect tissue abnormality caused by trigger finger. A self-developed image analysis system was used to avoid human subjectivity during the quantification process. Finally, correlations between the quantitative image parameters, pathological grading, and clinical severity classification were assessed. RESULTS: One-way ANOVA tests revealed significant correlations between the image quantification and pathological grading as well as between the image quantification and clinical severity classification. The Cohen’s kappa coefficient test also depicted good consistency between pathological grading and clinical severity classification. CONCLUSIONS: The criteria of clinical classification were found to be highly associated with the pathological changes of affected tissues. The correlations serve as explicit evidence supporting clinicians in making a treatment strategy of trigger finger. In addition, our proposed computer-aided image analysis system was considered to be a promising and objective approach to determining trigger finger severity at the microscopic level

The Relationship between Ischemic Stroke Patients with and without Retroflex Tongue: A Retrospective Study

Background. Patients suffering from stroke exhibit different levels of capability in retroflex tongues, in our clinical observation. This study aims to derive the association of tongue retroflexibility with the degree of severity for stroke patients. Methods. All ischemic stroke patients were collected from August 2010 to July 2013 in the Stroke Center, Changhua Christian Hospital, Taiwan. All participants underwent medical history collection and clinical examination, including tongue images captured by ATDS. Statistical analysis was performed to compare the differences of ischemic stroke patients with and without retroflex tongue. Result. Among the total of 308 cases collected, 123 patients cannot retroflex their tongues, that is, the non-RT group. The length of stay in the non-RT group, 32.0 ± 21.5, was longer than those of the RT counterparts, 25.9 ± 14.4 (p value: 0.007). The NIHSS on admission, 14.1 ± 7.8 versus 8.9 ± 5.2, was higher and the Barthel Index upon admission, 18.6 ± 20.7 and 35.0 ± 24.2, was lower for the non-RT patients than that of the RT counterparts. Also, the non-RT patients account for 60.2% and 75.6% for Barthel Index ≤ 17 and NIHSS ≥ 9, respectively. Conclusion. The stroke patients in non-RT group showed significantly poor prognosis and were more serious in the degree of severity and level of autonomy than RT group, indicating that the ability to maneuver tongue retroflex can serve as a simple, reliable, and noninvasive means for the prognosis of ischemic stroke patients

Significance of Coronary Calcification for Prediction of Coronary Artery Disease and Cardiac Events Based on 64-Slice Coronary Computed Tomography Angiography

This work aims to validate the clinical significance of coronary artery calcium score (CACS) in predicting coronary artery disease(CAD) and cardiac events in 100 symptomatic patients (aged 37–87 years, mean 62.5, 81 males) that were followed up for a mean of 5 years. Our results showed that patients with CAD and cardiac events had significantly higher CACS than those without CAD and cardiac events, respectively. The corresponding data were 1450.42 ± 3471.24 versus 130 ± 188.29 (P 1000. Increased CACS (>100)was also associated with an increased frequency of multi-vessel disease. Nonetheless, 3 (20%) out of 15 patients with zero CACS had single-vessel disease. Significant correlation (P < 0.001) was observed between CACS and CAD on a vessel-based analysis for coronary arteries. It is concluded that CACS is significantly correlated with CAD and cardiac events