Brain vessel status is a promising biomarker for better prevention and treatment in cerebrovascular disease. However, classic rule-based vessel segmentation algorithms need to be hand-crafted and are insufficiently validated. A specialized deep learning method—the U-net—is a promising alternative. Using labeled data from 66 patients with cerebrovascular disease, the U-net framework was optimized and evaluated with three metrics: Dice coefficient, 95% Hausdorff distance (95HD) and average Hausdorff distance (AVD). The model performance was compared with the traditional segmentation method of graph-cuts. Training and reconstruction was performed using 2D patches. A full and a reduced architecture with less parameters were trained. We performed both quantitative and qualitative analyses. The U-net models yielded high performance for both the full and the reduced architecture: A Dice value of ~0.88, a 95HD of ~47 voxels and an AVD of ~0.4 voxels. The visual analysis revealed excellent performance in large vessels and sufficient performance in small vessels. Pathologies like cortical laminar necrosis and a rete mirabile led to limited segmentation performance in few patients. The U-net outperfomed the traditional graph-cuts method (Dice ~0.76, 95HD ~59, AVD ~1.97). Our work highly encourages the development of clinically applicable segmentation tools based on deep learning. Future works should focus on improved segmentation of small vessels and methodologies to deal with specific pathologies.

The majority of MP3 players are sold with the earbud style of headphones. Preferred listening levels are higher with this style of headphone compared to the over-the-ear style. Moreover, as the noise level in the environment increases, earbud users are even more susceptible to background noise and consequently increase the level of the music to overcome this. The result is an increased sound pressure level at the eardrum. However, the levels chosen by our subjects suggest that MP3 listening levels may not be as significant a concern as has been reported recently in the mainstream media.

Radial forearm free flaps are a good reconstructive option after oropharyngeal cancer extirpation. Our acoustic and aeromechanical results indicated that issues related to quality of the speech signal require further study for resections of half or more than half of the soft palate.

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Wearable healthcare systems require skin‐adhering electrodes that allow maximal comfort for patients as well as an electronics system to enable signal processing and transmittance. Textile‐based electronics, known as “e‐textiles,” is a platform technology that allows comfort for patients. Here, two‐layered e‐textile patches are designed by controlled permeation of Ag‐particle/fluoropolymer composite ink into a porous textile. The permeated ink forms a cladding onto the nanofibers in the textile substrate, which is beneficial for mechanical and electrical properties of the e‐textile. The printed e‐textile features conductivity of ≈3200 S cm−1, whereas 1000 cycles of 30% uniaxial stretching causes the resistance to increase only by a factor of ≈5, which is acceptable in many applications. Controlling over the penetration depth enables a two‐layer design of the e‐textile, where the sensing electrodes and the conducting traces are printed in the opposite sides of the substrate. The formation of vertical interconnected access is remarkably simple as an injection from a syringe. With the custom‐developed electronic circuits, a surface electromyography system with wireless data transmission is demonstrated. Furthermore, the dry e‐textile patch collects electroencephalography with comparable signal quality to commercial gel electrodes. It is anticipated that the two‐layered e‐textiles will be effective in healthcare and sports applications.

Although a potentially morbid treatment, TGLP and free flap reconstruction can provide good swallowing and speech outcomes as well as meaningful long-term quality of life. Regular attendance of rehabilitation sessions is imperative to optimize functional outcomes.

Although some sensory ability is preserved in patients who have had tongue reconstruction with an innervated RFFF, functional outcomes such as masticatory ability and speech intelligibility may be affected in some patients.

The results of this study suggest that surgical reconstruction of the base of tongue using the radial forearm free flap in patients with large base of tongue lesions can lead to functional speech and swallowing results.