Approaches and Limitations of Machine Learning for Synthetic Ultrasound Generation: A Scoping Review
This scoping review examines the emerging field of synthetic ultrasound generation using
machine learning (ML) models in radiology. Nineteen studies were analyzed, revealing …
machine learning (ML) models in radiology. Nineteen studies were analyzed, revealing …
Single image super-resolution approaches in medical images based-deep learning: a survey
Abstract Medical image Super-Resolution (SR) reconstruction refers to the process of
regenerating a High-Resolution (HR) image from a degraded Low-Resolution (LR) image or …
regenerating a High-Resolution (HR) image from a degraded Low-Resolution (LR) image or …
Attention mechanism-based deep learning method for hairline fracture detection in hand X-rays
W Wang, W Huang, Q Lu, J Chen, M Zhang… - Neural Computing and …, 2022 - Springer
Wrist and finger fractures detection is always the weak point of associate study, because
there are small targets in X-rays, such as hairline fractures. In this paper, a dataset …
there are small targets in X-rays, such as hairline fractures. In this paper, a dataset …
Super-resolution of biomedical volumes with 2D supervision
Volumetric biomedical microscopy has the potential to increase the diagnostic information
extracted from clinical tissue specimens and improve the diagnostic accuracy of both human …
extracted from clinical tissue specimens and improve the diagnostic accuracy of both human …
Super-resolution techniques for biomedical applications and challenges
Super-resolution (SR) techniques have revolutionized the field of biomedical applications by
detailing the structures at resolutions beyond the limits of imaging or measuring tools. These …
detailing the structures at resolutions beyond the limits of imaging or measuring tools. These …
Semi-supervised leukocyte segmentation based on adversarial learning with reconstruction enhancement
The number, relative ratio, and appearance of peripheral blood leukocytes can assist
doctors to diagnose diseases such as lymphoma and leukemia. Therefore, segmentation of …
doctors to diagnose diseases such as lymphoma and leukemia. Therefore, segmentation of …
Progressive residual learning with memory upgrade for ultrasound image blind super-resolution
For clinical medical diagnosis and treatment, image super-resolution (SR) technology will be
helpful to improve the ultrasonic imaging quality so as to enhance the accuracy of disease …
helpful to improve the ultrasonic imaging quality so as to enhance the accuracy of disease …
BraNet: a mobil application for breast image classification based on deep learning algorithms
Y Jiménez-Gaona, MJR Álvarez… - Medical & Biological …, 2024 - Springer
Mobile health apps are widely used for breast cancer detection using artificial intelligence
algorithms, providing radiologists with second opinions and reducing false diagnoses. This …
algorithms, providing radiologists with second opinions and reducing false diagnoses. This …
Super-resolution reconstruction of ultrasound image using a modified diffusion model
Objective. This study aims to perform super-resolution (SR) reconstruction of ultrasound
images using a modified diffusion model, designated as the diffusion model for ultrasound …
images using a modified diffusion model, designated as the diffusion model for ultrasound …
人工智能在类器官研究中的应用进展与挑战
吴洪基， 王海霞， 汪玲， 罗小刚， 邹冬玲 - 中国癌症杂志, 2024 - china-oncology.com
类器官是一种优异的肿瘤和干细胞研究模型, 对其生长或药筛等过程的各种类型数据进行分析,
有助于提升对类器官本身以及所代表疾病的了解. 但人工观察和筛选类器官以及使用传统统计学 …
有助于提升对类器官本身以及所代表疾病的了解. 但人工观察和筛选类器官以及使用传统统计学 …