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Automatic Deep Learning-Based Pipeline for Automatic Delineation and Measurement of Fetal Brain Structures in Routine Mid-Trimester Ultrasound Images.

Fetal diagnosis and therapy
INTRODUCTION: The aim of this study was to develop a pipeline using state-of-the-art deep learning methods to automatically delineate and measure several of the most important brain structures in fetal brain ultrasound (US) images.

Artificial intelligence directed development of a digital twin to measure soft tissue shift during head and neck surgery.

PloS one
Digital twins derived from 3D scanning data were developed to measure soft tissue deformation in head and neck surgery by an artificial intelligence approach. This framework was applied suggesting feasibility of soft tissue shift detection as a hithe...

Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus.

International journal of computer assisted radiology and surgery
PURPOSE: Paranasal anomalies are commonly discovered during routine radiological screenings and can present with a wide range of morphological features. This diversity can make it difficult for convolutional neural networks (CNNs) to accurately class...

Shortening image registration time using a deep neural network for patient positional verification in radiotherapy.

Physical and engineering sciences in medicine
We sought to accelerate 2D/3D image registration computation time using image synthesis with a deep neural network (DNN) to generate digitally reconstructed radiographic (DRR) images from X-ray flat panel detector (FPD) images. And we explored the fe...

Current State of Artificial Intelligence in Clinical Applications for Head and Neck MR Imaging.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Due primarily to the excellent soft tissue contrast depictions provided by MRI, the widespread application of head and neck MRI in clinical practice serves to assess various diseases. Artificial intelligence (AI)-based methodologies, particularly dee...

Assessing the accuracy of ChatGPT references in head and neck and ENT disciplines.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: ChatGPT has gained popularity as a web application since its release in 2022. While artificial intelligence (AI) systems' potential in scientific writing is widely discussed, their reliability in reviewing literature and providing accurate r...

Diagnosis with confidence: deep learning for reliable classification of laryngeal dysplasia.

Histopathology
BACKGROUND: Diagnosis of head and neck (HN) squamous dysplasias and carcinomas is critical for patient care, cure, and follow-up. It can be challenging, especially for grading intraepithelial lesions. Despite recent simplification in the last WHO gra...

Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis.

Biomedical engineering online
PURPOSE: The contouring of organs at risk (OARs) in head and neck cancer radiation treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies have applied deep learning (DL) algorithms to automatically contour head and...