Deblurring masked image modeling for ultrasound image analysis
Recently, large pretrained vision foundation models based on masked image modeling
(MIM) have attracted unprecedented attention and achieved remarkable performance across …
(MIM) have attracted unprecedented attention and achieved remarkable performance across …
Using ultrasound image augmentation and ensemble predictions to prevent machine-learning model overfitting
EJ Snider, SI Hernandez-Torres, R Hennessey - Diagnostics, 2023 - mdpi.com
Deep learning predictive models have the potential to simplify and automate medical
imaging diagnostics by lowering the skill threshold for image interpretation. However, this …
imaging diagnostics by lowering the skill threshold for image interpretation. However, this …
Multi-source adversarial transfer learning for ultrasound image segmentation with limited similarity
Lesion segmentation of ultrasound medical images based on deep learning techniques is a
widely used method for diagnosing diseases. Although there is a large amount of ultrasound …
widely used method for diagnosing diseases. Although there is a large amount of ultrasound …
Ultrasound domain adaptation using frequency domain analysis
A common issue in exploiting simulated ultrasound data for training neural networks is the
domain shift problem, where the trained models on synthetic data are not generalizable to …
domain shift problem, where the trained models on synthetic data are not generalizable to …
Diagnosis of invasive pancreatic cancer in endoscopic ultrasound images leveraging translation models
K Seo, JH Lim, JS Park, MJ Yang, TJ Song… - … Signal Processing and …, 2025 - Elsevier
Background In guiding treatment decisions for pancreatic cancer, assessing vascular
invasion is critical, particularly for determining resectability. Deep learning techniques have …
invasion is critical, particularly for determining resectability. Deep learning techniques have …
Multi-task class feature space fusion domain adaptation network for thyroid ultrasound images: research on generalization of smart healthcare systems
In recent years, the poor generalizability of deep neural networks in multi-model medical
images has attracted widespread attention. Domain adaptation is an approach to alleviate …
images has attracted widespread attention. Domain adaptation is an approach to alleviate …
Moment-alignment domain adaptation in the few-shot and low-resource context
Domain adaptation is a powerful method for resolving data set shifts. This work applies a
state-of-the-art multisource domain adaptation method, moment-matching for multisource …
state-of-the-art multisource domain adaptation method, moment-matching for multisource …