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Ultrasonography

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Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.

BMC medical imaging
BACKGROUND: Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multicla...

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

International journal of computer assisted radiology and surgery
PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direc...

Development and validation of an ultrasound-based deep learning radiomics nomogram for predicting the malignant risk of ovarian tumours.

Biomedical engineering online
BACKGROUND: The timely identification and management of ovarian cancer are critical determinants of patient prognosis. In this study, we developed and validated a deep learning radiomics nomogram (DLR_Nomogram) based on ultrasound (US) imaging to acc...

MSK-TIM: A Telerobotic Ultrasound System for Assessing the Musculoskeletal System.

Sensors (Basel, Switzerland)
The aim of this paper is to investigate technological advancements made to a robotic tele-ultrasound system for musculoskeletal imaging, the MSK-TIM (Musculoskeletal Telerobotic Imaging Machine). The hardware was enhanced with a force feedback sensor...

Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy.

Nature communications
Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated...

An ultrasound-based ensemble machine learning model for the preoperative classification of pleomorphic adenoma and Warthin tumor in the parotid gland.

European radiology
OBJECTIVES: The preoperative classification of pleomorphic adenomas (PMA) and Warthin tumors (WT) in the parotid gland plays an essential role in determining therapeutic strategies. This study aims to develop and validate an ultrasound-based ensemble...

The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.

Scientific reports
Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed the Thyroid Imaging Reporting and Data System (TI-RADS) to standardize the interpretation and reporti...

A deep learning framework for identifying and segmenting three vessels in fetal heart ultrasound images.

Biomedical engineering online
BACKGROUND: Congenital heart disease (CHD) is one of the most common birth defects in the world. It is the leading cause of infant mortality, necessitating an early diagnosis for timely intervention. Prenatal screening using ultrasound is the primary...

Convolutional neural network deep learning model accurately detects rectal cancer in endoanal ultrasounds.

Techniques in coloproctology
BACKGROUND: Imaging is vital for assessing rectal cancer, with endoanal ultrasound (EAUS) being highly accurate in large tertiary medical centers. However, EAUS accuracy drops outside such settings, possibly due to varied examiner experience and fewe...