AIMC Topic: Ultrasonography

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Portable Ultrasound Bladder Volume Measurement Over Entire Volume Range Using a Deep Learning Artificial Intelligence Model in a Selected Cohort: A Proof of Principle Study.

Neurourology and urodynamics
OBJECTIVE: We aimed to prospectively investigate whether bladder volume measured using deep learning artificial intelligence (AI) algorithms (AI-BV) is more accurate than that measured using conventional methods (C-BV) if using a portable ultrasound ...

Technology advances in the placement of naso-enteral tubes and in the management of enteral feeding in critically ill patients: A narrative study.

Clinical nutrition ESPEN
Enteral feeding needs secure access to the upper gastrointestinal tract, an evaluation of the gastric function to detect gastrointestinal intolerance, and a nutritional target to reach the patient's needs. Only in the last decades has progress been a...

Development and Validation of Ultrasound Hemodynamic-based Prediction Models for Acute Kidney Injury After Renal Transplantation.

Academic radiology
RATIONALE AND OBJECTIVES: Acute kidney injury (AKI) post-renal transplantation often has a poor prognosis. This study aimed to identify patients with elevated risks of AKI after kidney transplantation.

Automated Microbubble Discrimination in Ultrasound Localization Microscopy by Vision Transformer.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound localization microscopy (ULM) has revolutionized microvascular imaging by breaking the acoustic diffraction limit. However, different ULM workflows depend heavily on distinct prior knowledge, such as the impulse response and empirical sele...

UltrasOM: A mamba-based network for 3D freehand ultrasound reconstruction using optical flow.

Computer methods and programs in biomedicine
BACKGROUND: Three-dimensional (3D) ultrasound (US) reconstruction is of significant value in clinical diagnosis, characterized by its safety, portability, low cost, and high real-time capabilities. 3D freehand ultrasound reconstruction aims to elimin...

Intra- and Peritumoral Radiomics Based on Ultrasound Images for Preoperative Differentiation of Follicular Thyroid Adenoma, Carcinoma, and Follicular Tumor With Uncertain Malignant Potential.

Ultrasound in medicine & biology
OBJECTIVE: Differentiating between follicular thyroid adenoma (FTA), carcinoma (FTC), and follicular tumor with uncertain malignant potential (FT-UMP) remains challenging due to their overlapping ultrasound characteristics. This retrospective study a...

Performance of radiomics analysis in ultrasound imaging for differentiating benign from malignant adnexal masses: A systematic review and meta-analysis.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: We present the state of the art of ultrasound-based machine learning (ML) radiomics models in the context of ovarian masses and analyze their accuracy in differentiating between benign and malignant adnexal masses.

Exploring Neural Dynamics in the Auditory Telencephalon of Crows Using Functional Ultrasound Imaging.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Crows, renowned for advanced cognitive abilities and vocal communication, rely on intricate auditory systems. While the neuroanatomy of corvid auditory pathways is partially explored, the underlying neurophysiological mechanisms are largely unknown. ...

Automatic Detection of B-Lines in Lung Ultrasound Based on the Evaluation of Multiple Characteristic Parameters Using Raw RF Data.

Ultrasonic imaging
B-line artifacts in lung ultrasound, pivotal for diagnosing pulmonary conditions, warrant automated recognition to enhance diagnostic accuracy. In this paper, a lung ultrasound B-line vertical artifact identification method based on radio frequency (...

A Deep Learning Model Based on High-Frequency Ultrasound Images for Classification of Different Stages of Liver Fibrosis.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: To develop a deep learning model based on high-frequency ultrasound images to classify different stages of liver fibrosis in chronic hepatitis B patients.