Ongoing improvements in AI, particularly concerning deep learning techniques, are
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …

Ultrasound (US) has become one of the most commonly performed imaging modalities in
clinical practice. It is a rapidly evolving technology with certain advantages and with unique …

Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

Purpose Delineation of thyroid nodule boundaries from ultrasound images plays an
important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it …

The use of computer-assisted analysis to improve image interpretation has been a long-
standing challenge in the medical imaging industry. In terms of image comprehension …

Background: This paper attempts to identify suitable Machine Learning (ML) approach for
image denoising of radiology based medical application. The Identification of ML approach …

Ultrasonography is a valuable diagnosis method for thyroid nodules. Automatically
discriminating benign and malignant nodules in the ultrasound images can provide aided …

Computerized prenatal ultrasound (US) image segmentation methods can greatly improve
the efficiency and objectiveness of the biometry interpretation. However, the boundary …

Importance Fetal ultrasonography is essential for confirmation of gestational age (GA), and
accurate GA assessment is important for providing appropriate care throughout pregnancy …

Image segmentation plays a critical role in the quantitative and qualitative analysis of
medical ultrasound images, directly affecting the follow-up analysis and processing …