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Automated Diagnosis and Classification of Temporomandibular Joint Degenerative Joint Disease via Artificial Intelligence Using CBCT Imaging.
J Dent
January 2025
Department of Oral & Maxillofacial Radiology, Peking University School & Hospital of Stomatology, Beijing 100081, China; National Center for Stomatology & National Clinical Research Center for Oral Diseases, Beijing 100081, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing 100081, China; Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China. Electronic address:
Objectives: In this study, artificial intelligence techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.
Methods: An AI model utilizing the YOLOv10 algorithm was trained, validated and tested on 7357 annotated and corrected oblique sagittal TMJ images (3010 images of normal condyles and 4347 images of condyles with DJD) from 1018 patients who visited Peking University School and Hospital of Stomatology for temporomandibular disorders and underwent TMJ CBCT examinations. This model could identify DJD as well as the radiographic signs of DJD, namely, erosion, osteophytes, sclerosis and subchondral cysts.
Calibration correction to improve registration during cone-beam CT guided histotripsy.
Med Phys
January 2025
Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Background: Histotripsy is a non-invasive, non-ionizing, non-thermal focused ultrasound technique. High amplitude short acoustic pulses converge to create high negative pressures that cavitate endogenous gas into a bubble cloud leading to mechanical tissue destruction. In the United States, histotripsy is approved to treat liver tumors under diagnostic ultrasound guidance but in initial clinical cases, some areas of the liver have not been treated due to bone or gas obstructing the acoustic window for targeting.
View Article and Find Full Text PDFInductive Power Transfer Coil Misalignment Perception and Correction for Wirelessly Recharging Underground Sensors.
Sensors (Basel)
January 2025
Department of Mechanical Engineering, University of Utah, Salt Lake City, UT 84112, USA.
Field implementations of fully underground sensor networks face many practical challenges that have limited their overall adoption. Power management is a commonly cited issue, as operators are required to either repeatedly excavate batteries for recharging or develop complex underground power infrastructures. Prior works have proposed wireless inductive power transfer (IPT) as a potential solution to these power management issues, but misalignment is a persistent issue in IPT systems, particularly in applications involving moving vehicles or obscured (e.
View Article and Find Full Text PDFAdvancing Hydrogel-Based 3D Cell Culture Systems: Histological Image Analysis and AI-Driven Filament Characterization.
Biomedicines
January 2025
Embrapa Genetic Resources and Biotechnology, Laboratory of Nanobiotechnology (LNANO), Brasília 70770-917, DF, Brazil.
Machine learning is used to analyze images by training algorithms on data to recognize patterns and identify objects, with applications in various fields, such as medicine, security, and automation. Meanwhile, histological cross-sections, whether longitudinal or transverse, expose layers of tissues or tissue mimetics, which provide crucial information for microscopic analysis. : This study aimed to employ the Google platform "Teachable Machine" to apply artificial intelligence (AI) in the interpretation of histological cross-section images of hydrogel filaments.
View Article and Find Full Text PDFCombining automation and expertise: A semi-automated approach to correcting eye-tracking data in reading tasks.
Behav Res Methods
January 2025
Department of Computer Science, Colby College, 4000 Mayflower Hill, Waterville, 04901, Maine, USA.
In reading tasks, drift can move fixations from one word to another or even another line, invalidating the eye-tracking recording. Manual correction is time-consuming and subjective, while automated correction is fast - yet limited in accuracy. In this paper, we present Fix8 (Fixate), an open-source GUI tool that offers a novel semi-automated correction approach for eye-tracking data in reading tasks.
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