Deep Learning-Based Multi-Class Segmentation of the Paranasal Sinuses of Sinusitis Patients Based on Computed Tomographic Images.

Accurate paranasal sinus segmentation is essential for reducing surgical complications through surgical guidance systems. This study introduces a multiclass Convolutional Neural Network (CNN) segmentation model by comparing four 3D U-Net variations-normal, residual, dense, and residual-dense. Data normalization and training were conducted on a 40-patient test set (20 normal, 20 abnormal) using 5-fold cross-validation. The normal 3D U-Net demonstrated superior performance with an F1 score of 84.29% on the normal test set and 79.32% on the abnormal set, exhibiting higher true positive rates for the sphenoid and maxillary sinus in both sets. Despite effective segmentation in clear sinuses, limitations were observed in mucosal inflammation. Nevertheless, the algorithm's enhanced segmentation of abnormal sinuses suggests potential clinical applications, with ongoing refinements expected for broader utility.

Development of an Automatic Pill Image Data Generation System.

OBJECTIVES: Since the easiest way to identify pills and obtain information about them is to distinguish them visually, many studies on image processing technology exist. However, no automatic system for generating pill image data has yet been developed. Therefore, we propose a system for automatically generating image data by taking pictures of pills from various angles. This system is referred to as the pill filming system in this paper. METHODS: We designed the pill filming system to have three components: structure, controller, and a graphical user interface (GUI). This system was manufactured with black polylactic acid using a 3D printer for lightweight and easy manufacturing. The mainboard controls data storage, and the entire process is managed through the GUI. After one reciprocating movement of the seesaw, the web camera at the top shoots the target pill on the stage. This image is then saved in a specific directory on the mainboard. RESULTS: The pill filming system completes its workflow after generating 300 pill images. The total time to collect data per pill takes 21 minutes and 25 seconds. The generated image size is 1280 × 960 pixels, the horizontal and vertical resolutions are both 96 DPI (dot per inch), and the file extension is .jpg. CONCLUSIONS: This paper proposes a system that can automatically generate pill image data from various angles. The pill observation data from various angles include many cases. In addition, the data collected in the same controlled environment have a uniform background, making it easy to process the images. Large quantities of high-quality data from the pill filming system can contribute to various studies using pill images.

Sparse Depth-Guided Image Enhancement Using Incremental GP with Informative Point Selection.

We propose an online dehazing method with sparse depth priors using an incremental Gaussian Process (iGP). Conventional approaches focus on achieving single image dehazing by using multiple channels. In many robotics platforms, range measurements are directly available, except in a sparse form. This paper exploits direct and possibly sparse depth data in order to achieve efficient and effective dehazing that works for both color and grayscale images. The proposed algorithm is not limited to the channel information and works equally well for both color and gray images. However, efficient depth map estimations (from sparse depth priors) are additionally required. This paper focuses on a highly sparse depth prior for online dehazing. For efficient dehazing, we adopted iGP for incremental depth map estimation and dehazing. Incremental selection of the depth prior was conducted in an information-theoretic way by evaluating mutual information (MI) and other information-based metrics. As per updates, only the most informative depth prior was added, and haze-free images were reconstructed from the atmospheric scattering model with incrementally estimated depth. The proposed method was validated using different scenarios, color images under synthetic fog, real color, and grayscale haze indoors, outdoors, and underwater scenes.

Design of Automatic Isolated Medical Waste Bin Cover for Drying Waste.

Background. The recent outbreak of COVID-19 has led to an increase in isolated medical waste, making the disposal of isolated medical waste a significant problem. There is the dedicated waste bin with four-sided locking-type at the top, causing contact during waste disposal. And it has infection possibility with high humidity. Purpose. In this article, we suggest automatic isolated medical waste bin cover for drying waste.

Association between Thyroid Function and Heart Rate Monitored by Wearable Devices in Patients with Hypothyroidism.

BACKGROUND: Heart rate (HR) monitored by a wearable device (WD) has demonstrated its clinical feasibility for thyrotoxicosis subjects. However, the association of HR monitored by wearables with hypothyroidism has not been examined. We assessed the association between serum thyroid hormone concentration and three WD-HR parameters in hypothyroid subjects. METHODS: Forty-four subjects scheduled for radioactive iodine therapy (RAI Tx) after thyroid cancer surgery were included. Thirty subjects were prepared for RAI Tx by thyroid hormone withdrawal (hypothyroidism group) and 14 subjects by recombinant human thyrotropin (control group). Three WD-HR parameters were calculated from the HR data collected during rest, during sleep, and from 2:00 AM to 6:00 AM, respectively. We analyzed the changes in conventionally measured resting HR (On-site rHR) and WDHR parameters relative to thyroid hormone levels. RESULTS: Serum free thyroxine (T4) levels, On-site rHR, and WD-HR parameters were lower in the hypothyroid group than in the control group at the time of RAI Tx. WD-HR parameters also reflected minute changes in free T4 levels. A decrease in On-site rHR and WD-HR parameters by one standard deviation (On-site rHR, approximately 12 bpm; WD-HR parameters, approximately 8 bpm) was associated with a 0.2 ng/dL decrease in free T4 levels (P<0.01) and a 2-fold increase of the odds ratio of hypothyroidism (P<0.01). WD-HR parameters displayed a better goodness-of-fit measure (lower quasi-information criterion value) than On-site rHR in predicting the hypothyroidism. CONCLUSION: This study identified WD-HR parameters as informative and easy-to-measure biomarkers to predict hypothyroidism.

Design of Automatic Hand Sanitizer System Compatible with Various Containers.

OBJECTIVE: Demand for hand sanitizers has surged since the coronavirus broke out and spread around the world. Hand sanitizers are usually applied by squirting the sanitizer liquid when one presses a pump with one's hand. This causes many people to come into contact with the pump handle, which increases the risk of viral transmission. Some hand sanitizers on the market are automatically pumped. However, because sanitizer containers and pump devices are designed to be compatible only between products produced by the same manufacturer, consumers must also repurchase the container for the liquid if they replace the hand sanitizer. Therefore, this paper suggests the design of an automatic hand sanitizer system compatible with various sanitizer containers. METHODS: An automatic hand sanitizer system was designed, which will be presented in two stages describing the instrument structure and control parts. This work focused on using the elasticity of pumps and improving people's access to devices. RESULTS: We have designed an automatic hand sanitizer system that is compatible with various containers. When one moves one's hand close to the device sensor, the hand sanitizer container is pumped once. CONCLUSION: The automatic hand sanitizer device proposed in this paper is ultimately expected to contribute to contactless hand disinfection in public places and virus infection prevention. Additionally, it is economical and eco-friendly by decreasing waste emissions.