Detection of Macula and Recognition of Aged-Related Macular Degeneration in Retinal Fundus Images

In aged people, the central vision is affected by Age-Related Macular Degeneration (AMD). From the digital retinal fundus images, AMD can be recognized because of the existence of Drusen, Choroidal Neovascularization (CNV), and Geographic Atrophy (GA). It is time-consuming and costly for the ophthalmologists to monitor fundus images. A monitoring system for automated digital fundus photography can reduce these problems. In this paper, we propose a new macula detection system based on contrast enhancement, top-hat transformation, and the modified Kirsch template method. Firstly, the retinal fundus image is processed through an image enhancement method so that the intensity distribution is improved for finer visualization. The contrast-enhanced image is further improved using the top-hat transformation function to make the intensities level differentiable between the macula and different sections of images. The retinal vessel is enhanced by employing the modified Kirsch's template method. It enhances the vasculature structures and suppresses the blob-like structures. Furthermore, the OTSU thresholding is used to segment out the dark regions and separate the vessel to extract the candidate regions. The dark region and the background estimated image are subtracted from the extracted blood vessels image to obtain the exact location of the macula. The proposed method applied on 1349 images of STARE, DRIVE, MESSIDOR, and DIARETDB1 databases and achieved the average sensitivity, specificity, accuracy, positive predicted value, F1 score, and area under curve of 97.79 %, 97.65 %, 97.60 %, 97.38 %, 97.57 %, and 96.97 %, respectively. Experimental results reveal that the proposed method attains better performance, in terms of visual quality and enriched quantitative analysis, in comparison with eminent state-of-the-art methods

Inguinal Hernia Repair on Day Care Basis During Global COVID-19 Pandemic

  Abstract Background: COVID-19 has effected General Surgical Elective list and most of the surgical procedures are postpone. Inguinal hernia surgery can be performed under local anesthesia on day care basis in selected group of patients taking all necessary precautions for COVID-19. Patients & Methods: This prospective study was conducted at department of General Surgery Federal Hospital, Islamabad for a period of three months from 15th March 2020 to 15th June 2020. All patients were included in the study through purposive sampling and preference was given to patients elder than 50 years of age. This study included 59 adult patients with inguinal hernia who under mesh repair under local anaesthesia on day care basis. Results: A total of 59 patients were included in the study. All patients were male. The age range was from 37 to 82 years (SD=± 10.23).  30 (50.84%) patient had inguinal hernia on left side while 26 (44.06%) had hernia on right side. Mean Operative time was 35 min. Pain was chief complaint postoperatively 30 (50.8%) patients had moderate pain while 6 (10.1%) patients had severe pain in first 24 hours after surgery. Fever was present in 15 (25.42%) patients in first 24 hours. All patients were negative for COVID -19 preoperatively and after 2 weeks none of the patients develop any symptoms of COVID-19. 3 (5.08%) patients needed readmission within 24 hours for pain and some haemorrhage. There was no mortality in our study Conclusions: Inguinal Hernia Surgery under local anaesthesia on day care basis in a very good practice at this time of global pandemic of COVID-19. This is a safe and reliable strategy. Key words: Inguinal Hernia, COVID-19, Local Anaesthesia &nbsp

Surgical Outcome of Subdural Hematoma by Single Vs Double Burr Hole Technique

Objective: To determine frequency of a favorable outcome of chronic subdural hematoma patients by single vs. double burr hole technique.Materials and Methods: A randomized controlled trial was done in Neurosurgery Department, Pakistan Institute of Medical Sciences, Islamabad from 15th September 2016 to 15th August 2017. All patients in group A were operated through a single burr-hole technique either under general anesthesia or local. Group B patients were operated through double burr-hole technique.Results: One hundred patients were included in this study, divided into two groups. Group A had mean age 54 years with STD of ± 5.7 while in group B, mean age was 53 years with STD of ± 6.3. In group A there were 35 (70%) male and 15 (30%) female patients while group B had 30 (60%) male and 20 (40%) female patients. In group A, mean GCS was 12.78 with STD of ± 1.4. In group B, mean GCS was 12.64 with STD of ± 1.3. The favorable outcome after surgery was attained in 43 (86%) patients in Group A while 46 (92%) patients in Group B.Conclusion: Chronic subdural hematoma is a complication seen in older age after trivial trauma history. Single burr-hole drainage of hematoma is an effective method of treatment when compared with double burr-hole method which is more time consuming

AI safety of film capacitors.

With a large number of film capacitors being deployed in critical locations in electrical and electronic systems, artificial intelligence (AI) technology is also expected to address the problems encountered in this process. According to our findings, AI applications can cover the entire lifecycle of film capacitors. However, the AI safety hazards in these applications have not received the attention they deserve. To meet this, the authors argue, with specific examples, risks that flawed, erratic, and unethical AI can introduce in the design, operation, and evaluation of film capacitors. Human-AI common impact and more multi-dimensional evaluation for AI are proposed to better cope with unknown, ambiguity, and known risks brought from AI in film capacitors now and in the future

Data sonification of film capacitors.

Film capacitors are playing an increasingly important role in power-related fields, driven by the continuous development of dielectric materials and practical needs. Long-term accumulation has also led to an increasing wealth of data related to film capacitors. Sonification opens up a new way for people to make good use of data from film capacitors. A framework for sonifying film capacitors data based on TwoTone is presented. Based on the analysis and discussion, it is clear that the sonification results can easily represent the monotonic variation pattern of film capacitors data. What's more, the sonification results increase the possibility that people pay attention to the changing trend of film capacitors data when there is no significant difference in the visual perception of the data. In addition to providing a new way of music generation of electrical equipment, the method proposed is expected to contribute to theory reference in typical scenarios, such as factory calibration of film capacitors, monitoring of film capacitor operation status, and presentation of statistical data of film capacitors' dielectric materials, which will help us to better understand the distribution characteristics of polymer films

Advanced Techniques for the Processing of Ship Data Collected Onboard Through Innovative Inspection Techniques

Ships structural condition is assessed regularly to maintain safety operations at sea, avoid casualties and economic losses. Traditionally, structural integrity assessment is performed physically through ship surveyors, requiring complex and time-consuming operations to access to any space of the ship, including narrow confined spaces and elevated areas. Imagery based, three-dimensional (3D) reconstruction of vessel structures is a new notable area that is obtaining considerable interest both in commercial and scientific sectors. It can provide a low-cost, less disruptive and safer ship inspection approach. In the present research, an alternative technology to generate 3D models, based on camera photos taken by drones, is explored. Aim of the present work is to highlight how human made ship surveys can be improved by using robotics technology. Hence, a procedure for 3D reconstruction with combined use of photogrammetry/videogrammetry and computer vision techniques is developed, after several field trials, providing an alternative to ease vessel inspections. The effect of pre-processing of image datasets aimed at improving the performance of 3D reconstruction is investigated. An efficient image pre-processing pipeline is presented, based on computer vision algorithms for color enhancement, shadow removal and image blurriness. This research makes a significant contribution by developing hierarchical learning approaches and analyzing current architectures in the field of defect recognition, namely cracks and corrosion, particularly in marine structures. Developing an image-based algorithm that can detect corrosion damage in a sequence of digital photos is a viable solution to solve the aforementioned shortcomings. After making 3D models, by using computer vision algorithms, in this research we propose a new approach to expedite crack and corrosion detection, visualize the cracks efficiently in ship structures and then measure their length. The process includes two parts: at first, crack images are captured manually by using low-cost handheld cameras. Afterward, image is imported into software and processed. To make analysis easier, image is compressed and converted into grayscale. Image contrast is then stretched to enhance the contrast between background and crack. After obtaining latent crack identification features, images are elaborated by preprocessing, feature extraction, image segmentation, thus estimating the region of interest and determining whether the image includes a crack or not. A big dataset of photos of corroded images was used to test the algorithm. Our findings suggest that the algorithm we created is capable of locating corroded spots quickly. In the last section of this research, we discuss and analyze two methods for obtaining point cloud models for detecting and visualizing the condition of a ship's structure in maritime projects: (I) a new approach of automated image-based reconstruction and design of a ship structure is developed, through evaluation of Structure from Motion (SfM); (II) Through 3D laser scanning, dense point cloud models were created and analyzed. An analysis of the newly created automatic image-based reconstruction approach as well as exclusive features approaches is discussed. The terrestrial laser scanning technique is then demonstrated for reconstruction as well as comparison of as-built scenes. These methodologies give a reliable way to track progress, quality and productivity on a survey site. Finally, both strategies were evaluated for their accuracy and usability in the reconstruction and automated generation of point cloud models. This study can help in an effective and reliable decision-making process, due to its user-friendly and cost effectiveness, mainly for large cargo holds requiring frequent assessment because of cargo operations induced damages