Development of Periapical Index Score Classification System in Periapical Radiographs Using Deep Learning.

Periapical index (PAI) scoring system is the most popular index for evaluating apical periodontitis (AP) on radiographs. It provides an ordinal scale of 1 to 5, ranging from healthy to severe AP. Scoring PAI is a time-consuming process and requires experienced dentists; thus, deep learning has been applied to hasten the process.

A Comparison of Deep Learning vs. Dental Implantologists in Cone-Beam Computed Tomography-Based Bone Quality Classification.

Bone quality assessment is crucial for pre-surgical implant planning, influencing both implant design and drilling protocol selection. The Lekholm and Zarb (L&Z) classification, which categorizes bone quality into four types based on cortical bone width and trabecular bone density using cone-beam computed tomography (CBCT) data, lacks quantitative guidelines, leading to subjective interpretations. This study aimed to compare the performance of deep learning (DL)-based approaches against human examiners in assessing bone quality, according to the L&Z classification, using CBCT images.

CrossViT with ECAP: Enhanced deep learning for jaw lesion classification.

Background: Radiolucent jaw lesions like ameloblastoma (AM), dentigerous cyst (DC), odontogenic keratocyst (OKC), and radicular cyst (RC) often share similar characteristics, making diagnosis challenging. In 2021, CrossViT, a novel deep learning approach using multi-scale vision transformers (ViT) with cross-attention, emerged for accurate image classification. Additionally, we introduced Extended Cropping and Padding (ECAP), a method to expand training data by iteratively cropping smaller images while preserving context.

Deep learning-based super-resolution of structural brain MRI at 1.5 T: application to quantitative volume measurement.

Objective: This study investigated the feasibility of using deep learning-based super-resolution (DL-SR) technique on low-resolution (LR) images to generate high-resolution (HR) MR images with the aim of scan time reduction. The efficacy of DL-SR was also assessed through the application of brain volume measurement (BVM).

Materials And Methods: In vivo brain images acquired with 3D-T1W from various MRI scanners were utilized.

Feasibility Study of a Prototype Wearable Inertial Measurement Unit for Elderly Postural Sway Assessment.

Background: Falls are a major public health problem among older adults since they are a primary cause of injuries, functional decline and mortality. Identifying individuals susceptible to falls enables early intervention and prevention strategies. Currently, wearable sensors have emerged as a promising tool for assessing balance and mobility due to their affordability, compact size, and established efficacy.

Does Articular Disc Position Change Following Mandibular Setback Surgery?

Background: Maintaining condyle position following bilateral sagittal split ramus osteotomy (BSSO) is crucial to minimizing postoperative relapse. However, the impact of BSSO on the articular disc position remains inconclusive.

Purpose: This study aimed to investigate the changes in articular disc position following setback BSSO surgery.

Enhancing Caries Detection in Bitewing Radiographs Using YOLOv7.

The study aimed to evaluate the impact of image size, area of detection (IoU) thresholds and confidence thresholds on the performance of the YOLO models in the detection of dental caries in bitewing radiographs. A total of 2575 bitewing radiographs were annotated with seven classes according to the ICCMS radiographic scoring system. YOLOv3 and YOLOv7 models were employed with different configurations, and their performances were evaluated based on precision, recall, F1-score and mean average precision (mAP).

A web application for sex and stature estimation from radiographic proximal femur for a Thai population.

In both forensic and archaeological domains, the discovery of incomplete human remains is a frequent occurrence. Nevertheless, the estimation of biological profiles from such remains presents a challenge due to the absence of crucial skeletal elements, such as the skull and pelvis. This study aimed to assess the utility of the proximal femur in the forensic identification process by creating a web application for osteometric analysis of the proximal femur.

Effects of manual therapy combined with therapeutic exercise versus routine physical therapy on brain biomarkers in patients with chronic non-specific neck pain in Thailand: a study protocol for a single-blinded randomised controlled trial.

Introduction: Structural brain alterations in pain-related areas have been demonstrated in patients with non-specific neck pain. While manual therapy combined with therapeutic exercise is an effective management for neck pain, its underlying mechanisms are poorly understood. The primary objective of this trial is to investigate the effects of manual therapy combined with therapeutic exercise on grey matter volume and thickness in patients with chronic non-specific neck pain.

Variability of gait characteristics in lameness elephant.

Lameness has a significant impact not only on the economy but also on elephant welfare. Several gait characteristics are altered to compensate for the discomfort. The traditional approach to detecting lameness has relied on mahout and veterinarian observation.

Feasibility of deep learning for dental caries classification in bitewing radiographs based on the ICCMS™ radiographic scoring system.

Objective: To evaluate the potential of deep learning models for categorization of dental caries in bitewing radiographs based on the International Caries Classification and Management System (ICCMS™) radiographic scoring system (RSS).

Study Design: In total, 2758 annotated bitewing radiographs were randomly divided into 3 experiments to assess the ResNet-18, -50, -101, and -152. Experiment A tested 4-class ICCMS™-RSS training and validation using Carestream (CS) radiographs; experiment B tested training and validation using CS and VistaScan radiographs; experiment C tested 7-class ICCMS™-RSS training and validation using CS and VistaScan radiographs.

Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS™ radiographic scoring system.

Objectives: To assess the feasibility of the YOLOv3 model under the intersection over union (IoU) thresholds of 0.5 (IoU) and 0.75 (IoU) for caries detection in bitewing radiographs based on the International Caries Classification and Management System (ICCMS™).

Development of a Protocol for Biomechanical Gait Analysis in Asian Elephants Using the Triaxial Inertial Measurement Unit (IMU).

Gait analysis is a method of gathering quantitative information to assist in determining the cause of abnormal gait for the purpose of making treatment decisions in veterinary medicine. Recent technology has offered the wearable wireless sensor of an inertial measurement unit (IMU) for determining gait parameters. This study proposed the use of a triaxial IMU, comprising an accelerometer, a gyroscope, and a magnetometer, for detecting three-dimensional limb segment motion ( axis) during the gait cycle in Asian elephants.

Pentagalloyl Glucose and Cisplatin Combination Treatment Exhibits a Synergistic Anticancer Effect in 2D and 3D Models of Head and Neck Carcinoma.

Although cisplatin is a first-line chemotherapy drug for head and neck squamous cell carcinoma (HNSCC), its therapeutic efficacy is limited owing to serious side effects and acquired drug resistance. This study determined whether combining pentagalloyl glucose (PGG) and cisplatin enhanced their anti-tumor activities on HNSCC cell lines. We investigated the anticancer effect of PGG combined with cisplatin in 2D and 3D multicellular spheroid cell culture.

Application of Machine Learning to Predict Trajectory of the Center of Pressure (COP) Path of Postural Sway Using a Triaxial Inertial Sensor.

Postural sway indicates controlling stability in response to standing balance perturbations and determines risk of falling. In order to assess balance and postural sway, costly laboratory equipment is required, making it impractical for clinical settings. The study aimed to develop a triaxial inertial sensor and apply machine learning (ML) algorithms for predicting trajectory of the center of pressure (COP) path of postural sway.

An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.

Background: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from the liver region. However, only user-defined liver region remained a manual process.

Impact of Weight Carriage on Joint Kinematics in Asian Elephants Used for Riding.

Background: Elephants in Thailand have changed their roles from working in the logging industry to tourism over the past two decades. In 2020, there were approximately 2700 captive elephants participating in activities such as riding and trekking. During work hours, riding elephants carry one or two people in a saddle on the back with a mahout on the neck several hours a day and over varying terrain.

Feasibility of accelerated 3D T1-weighted MRI using compressed sensing: application to quantitative volume measurements of human brain structures.

Objective: Scan time reduction is necessary for volumetric acquisitions to improve workflow productivity and to reduce motion artifacts during MRI procedures. We explored the possibility that Compressed Sensing-4 (CS-4) can be employed with 3D-turbo-field-echo T1-weighted (3D-TFE-T1W) sequence without compromising subcortical measurements on clinical 1.5 T MRI.

Automatic cardiac T2* relaxation time estimation from magnetic resonance images using region growing method with automatically initialized seed points.

Background And Objective: Heart failure due to iron-overload cardiomyopathy is one of the main causes of mortality. The cardiomyopathy is reversible if intensive iron chelation treatment is done in time, but the diagnosis is often delayed because the cardiac iron deposition is unpredictable and the symptoms are lately detected. There are many ways to assess iron-overload.