Caliper navigation for craniotomy planning of convexity targets

Introduction A technique to localize a radiological target on the head convexity fast and with acceptable precision is sufficient for surgeries of superficial intracranial lesions, and of help in the setting of emergency surgery, computer navigation breakdown, limited resources and education. We present a caliper technique based on fundamental geometry, with inexpensive and globally available tools (conventional CT or MRI image viewer, calculator, caliper). Methods The distances of the radiological target from two landmarks (nasion and porus acusticus externus) are assessed with an image viewer and Pythagoras’ theorem. The two distances are then marked around the landmarks onto the head of the patient with help of a caliper. The intersection defines the target. We tested the technique in a saw bone skull model and afterwards in the operating room. Convexity targets were localized with the caliper navigation technique and then with computer navigation as ground truth. Results In the saw bone model, the mean offset between the caliper navigated target and the real target was 2.9 ± 2.8 mm, 95% CI (1.6 mm; 4.2 mm). The mean offset between computer navigated target and real target was 1.6 ± 0.9 mm, 95% CI (1.2 mm; 2 mm) (ns). In 15 patients undergoing navigated cranial procedures, 100 targets were assessed in reference to computer navigation. The mean offset of the caliper navigation was 11 ± 5.2 mm, 95% CI (9.9 mm; 12 mm). Conclusion This is a low-tech approach for translation of a radiological target to the patient’s head in short time and with globally available inexpensive tools, with satisfying precision for many procedures.

Connection status report generator

This paper presents “Connection Status Report Generator” which is an auto executable application and it generates a detailed textual and pictorial representation of the network connectivity status of a particular computer and sends the generated reports to the concerned party. The features developed in this paper aim to constantly monitor the network connectivity status as well as ease the troubleshooting process of finding the major cause of call-drops which is a popular problem in every industry. This paper is divided into three major sub-categories of real-time connection status tracker, report generator, and the image viewer interface. The proposed executable application is coded in Java and designed to run as a background application with minimal system prerequisites.

Learning to see with Deleuze: understanding affective responses in image-viewer research assemblages

I describe an approach to analysing the affective flows produced in sociomaterial assemblages of visual images and humans in research processes. The approach combines Deleuzian understandings of repetition and difference, and of lines of articulation and flight, with interpretative techniques drawn from visual social semiotics. I use examples from my research into images shared by professionals on Twitter to illustrate how this approach can reveal not only the forces, intensities and hidden logics that lead to particular responses, but also the ways in which these responses impact on research decisions and interpretations.

Evaluating Usability of a Touchless Image Viewer in the Operating Room

Background Availability of patient-specific image data, gathered from preoperatively conducted studies, like computed tomography scans and magnetic resonance imaging studies, during a surgical procedure is a key factor for surgical success and patient safety. Several alternative input methods, including recognition of hand gestures, have been proposed for surgeons to interact with medical image viewers during an operation. Previous studies pointed out the need for usability evaluation of these systems. Objectives We describe the accuracy and usability of a novel software system, which integrates gesture recognition via machine learning into an established image viewer. Methods This pilot study is a prospective, observational trial, which asked surgeons to interact with software to perform two standardized tasks in a sterile environment, modeled closely to a real-life situation in an operating room. To assess usability, the validated “System Usability Scale” (SUS) was used. On a technical level, we also evaluated the accuracy of the underlying neural network. Results The neural network reached 98.94% accuracy while predicting the gestures during validation. Eight surgeons with an average of 6.5 years of experience participated in the usability study. The system was rated on average with 80.25 points on the SUS. Conclusion The system showed good overall usability; however, additional areas of potential improvement were identified and further usability studies are needed. Because the system uses standard PC hardware, it made for easy integration into the operating room.