Objective Chronic venous disease is a common vascular condition, affecting up to 60% of the population worldwide. In Australia and New Zealand, chronic venous insufficiency ultrasound examinations are primarily performed by sonographers. This research aimed to explore how ultrasound examinations are being performed, providing insights into current practices and recommendations for quality improvement. Method A questionnaire was distributed to capture demographics, practices of ultrasound, examination techniques, the use of nomenclature and experience of the respondents. Results The analysis of 97 responses showed a heterogeneity in the clinical application of ultrasound. Most sonographers performed less than two scans per day within 30–45 minutes. Deep venous incompetence was routinely excluded by all respondents. The majority used standing, sitting and reverse Trendelenburg position except for a few using supine position. Manual augmentation was the preferred provocation manoeuvre. Anatomical variations at the junctional level were not adequately evaluated. Although Giacomini’s vein was assessed by 80%, 57% of those did not evaluate paradoxical reflux. Seventy-five per cent routinely assessed non-saphenous reflux; however, over 50% were unfamiliar with lymph node venous networks. A significant number of out-dated venous terms were still being used. A low participation rate in continuing professional development was identified, which might be attributable to limited education and training programs. Conclusion The study is a multi-faceted exploration that identified a need for standardized diagnostic and reporting guidelines. Our results could explain discrepancies in diagnostic findings and inconsistencies in the use of medical terminology, with implications for clinical decision making and assessment of surgical outcome.
Space-based target surveillance is important for aerospace safety. However, with the increasing complexity of the space environment, the stellar target and strong noise interference pose difficulties for space target detection. Simultaneously, it is hard to balance real-time processing with computational performance for the onboard processing platform owing to resource limitations. The heterogeneous multi-core architecture has corresponding processing capabilities, providing a hardware implementation platform with real-time and computational performance for space-based applications. This paper first developed a multi-stage joint detection and tracking model (MJDTM) for space targets in optical image sequences. This model combined an improved local contrast method and the Kalman filter to detect and track the potential targets and use differences in movement status to suppress the stellar targets. Then, a heterogeneous multi-core processing system based on a field-programmable gate array (FPGA) and digital signal processor (DSP) was established as the space-based image processing system. Finally, MJDTM was optimized and implemented on the above image processing system. The experiments conducted with simulated and actual image sequences examine the accuracy and efficiency of the MJDTM, which has a 95% detection probability while the false alarm rate is 10−4. According to the experimental results, the algorithm hardware implementation can detect targets in an image with 1024 × 1024 pixels in just 22.064 ms, which satisfies the real-time requirements of space-based surveillance.
Background: Duplex ultrasound is the first line of investigation for patients seeking treatment for varicose veins disease. In Australia, chronic venous insufficiency ultrasound examinations (CVI-US) are primarily performed by sonographers. The use of clinical guidelines facilitates the practice of ultrasound, and more importantly, provides an assurance to the integrity and quality of the examinations. Our aim is to assess the quality of currently available guidelines and provide recommendations for choosing the appropriate guideline to use and suggestions for future guideline development. Method: We performed a systematic literature search of the Cochrane, EMBASE, EBSCO, Medline, PubMed, Google and the database of the University of Sydney. The scope covered guidelines from 2000 to 2020 available in English. Identified guidelines were appraised by four independent reviewers (sonographers) using the revised version of the Appraisal of Guidelines Research and Evaluation instrument. Results: A total of 10 guidelines were included for critical appraisal. Analysis of the results showed most guidelines were rated low quality except for the International Union of Phlebology consensus document (2006) and technical guideline by Zygmunt and colleagues (2020). Overall, Domain 1 (Scope and purposes) achieved the highest score (total score = 67.9% ± 17.3%), whereas, Domain 3 (Rigour of development) had the lowest score (total score = 41.1% ± 13.5%). Conclusion:The overall quality of CVI-US guidelines is poor. This study highlights the demand for developing ultrasound guidelines based on methodologically sound principles along with updated scientific evidence. A stronger emphasis should be given to clinical applicability in the Australian context.
This paper addresses the problem of instance-level 6DoF pose estimation from a single RGBD image in an indoor scene. Many recent works have shown that a two-stage network, which first detects the keypoints and then regresses the keypoints for 6d pose estimation, achieves remarkable performance. However, the previous methods concern little about channel-wise attention and the keypoints are not selected by comprehensive use of RGBD information, which limits the performance of the network. To enhance RGB feature representation ability, a modular Split-Attention block that enables attention across feature-map groups is proposed. In addition, by combining the Oriented FAST and Rotated BRIEF (ORB) keypoints and the Farthest Point Sample (FPS) algorithm, a simple but effective keypoint selection method named ORB-FPS is presented to avoid the keypoints appear on the non-salient regions. The proposed algorithm is tested on the Linemod and the YCB-Video dataset, the experimental results demonstrate that our method outperforms the current approaches, achieves ADD(S) accuracy of 94.5% on the Linemod dataset and 91.4% on the YCB-Video dataset.
The intelligent laboratory is an important carrier for the development of the manufacturing industry. In order to meet the technical state requirements of the laboratory and control the particle redundancy, the wearing state of personnel and the technical state of objects are very important observation indicators in the digital laboratory. We collect human and object state datasets, which present the state classification challenge of the staff and experimental tools. Humans and objects are especially important for scene understanding, especially those existing in scenarios that have an impact on the current task. Based on the characteristics of the above datasets—small inter-class distance and large intra-class distance—an attention-based branch expansion network (ABE) is proposed to distinguish confounding features. In order to achieve the best recognition effect by considering the network’s depth and width, we firstly carry out a multi-dimensional reorganization of the existing network structure to explore the influence of depth and width on feature expression by comparing four networks with different depths and widths. We apply channel and spatial attention to refine the features extracted by the four networks, which learn “what” and “where”, respectively, to focus. We find the best results lie in the parallel residual connection of the dual attention applied in stacked block mode. We conduct extensive ablation analysis, gain consistent improvements in classification performance on various datasets, demonstrate the effectiveness of the dual-attention-based branch expansion network, and show a wide range of applicability. It achieves comparable performance with the state of the art (SOTA) on the common dataset Trashnet, with an accuracy of 94.53%.
The assessment of the saphenofemoral junction (SFJ) is important in the diagnosis and treatment of venous reflux of the great saphenous vein (GSV). In the clinical practice of venous medicine, the SFJ is used to represent the region at which the saphenous arch connects with the common femoral vein (CFV). A number of notable variations of the SFJ have been documented, and rare variable courses of the GSV have been described recently. Our case study reports two unusual GSV terminations. In both cases, the SFJ was located below the confluence of the profunda femoris vein (PFV) with the femoral vein (FV). Case 1 showed the SFJ was formed by the GSV and FV; whereas case 2 showed the PFV was joined by the GSV after a transposition with the FV. Anatomical variations of the SFJ are rare; however, they are increasingly diagnosed with the use of duplex ultrasound. The identification of SFJ variants warrants a safe endovenous procedure and prevents surgical complications.
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