AI Medical Compendium Topic:
Ultrasonography

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Breast nodule classification with two-dimensional ultrasound using Mask-RCNN ensemble aggregation.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to create a deep learning algorithm to infer the benign or malignant nature of breast nodules using two-dimensional B-mode ultrasound data initially marked as BI-RADS 3 and 4.

IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound.

IEEE transactions on medical imaging
We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle...

Generating Synthetic Labeled Data From Existing Anatomical Models: An Example With Echocardiography Segmentation.

IEEE transactions on medical imaging
Deep learning can bring time savings and increased reproducibility to medical image analysis. However, acquiring training data is challenging due to the time-intensive nature of labeling and high inter-observer variability in annotations. Rather than...

Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams.

Nature communications
Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates. In this work, we present an AI system that achieves radiologist-level accuracy in identifying breast cancer in ul...

An Unsupervised Learning-Based Multi-Organ Registration Method for 3D Abdominal CT Images.

Sensors (Basel, Switzerland)
Medical image registration is an essential technique to achieve spatial consistency geometric positions of different medical images obtained from single- or multi-sensor, such as computed tomography (CT), magnetic resonance (MR), and ultrasound (US) ...

Ultrasound Image Features under Deep Learning in Breast Conservation Surgery for Breast Cancer.

Journal of healthcare engineering
This study was to analyze the effect of the combined application of deep learning technology and ultrasound imaging on the effect of breast-conserving surgery for breast cancer. A deep label distribution learning (LDL) model was designed, and the sem...

Modality-agnostic self-supervised deep feature learning and fast instance optimisation for multimodal fusion in ultrasound-guided interventions.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fast and robust alignment of pre-operative MRI planning scans to intra-operative ultrasound is an important aspect for automatically supporting image-guided interventions. Thus far, learning-based approaches have failed to t...

A CNN-based method to reconstruct 3-D spine surfaces from US images in vivo.

Medical image analysis
Three-dimensional (3-D) reconstruction of the spine surface is of strong clinical relevance for the diagnosis and prognosis of spine disorders and intra-operative image guidance. In this paper, we report a new technique to reconstruct lumbar spine su...

Simultaneous Segmentation of Fetal Hearts and Lungs for Medical Ultrasound Images via an Efficient Multi-scale Model Integrated With Attention Mechanism.

Ultrasonic imaging
Large scale early scanning of fetuses via ultrasound imaging is widely used to alleviate the morbidity or mortality caused by congenital anomalies in fetal hearts and lungs. To reduce the intensive cost during manual recognition of organ regions, man...