Harnessing chemically crosslinked microbubble clusters using deep learning for ultrasound contrast imaging [0.03%]
基于深度学习的化学交联微气泡团簇用于超声造影成像技术研究
Teja Pathour,Ghazal Rastegar,Shashank R Sirsi et al.
Teja Pathour et al.
Purpose: We aim to investigate and isolate the distinctive acoustic properties generated by chemically crosslinked microbubble clusters (CCMCs) using machine learning (ML) techniques, specifically using an anomaly detecti...
Influence of phantom design on evaluation metrics in photon counting spectral head CT: a simulation study [0.03%]
CT谱物理学 phantom设计对光子计数头部CT评价指标影响的仿真研究
Bahaa Ghammraoui,Mridul Bhattarai,Harsha Marupudi et al.
Bahaa Ghammraoui et al.
Purpose: Accurate iodine quantification in contrast-enhanced head CT is crucial for precise diagnosis and treatment planning. Traditional CT methods, which use energy-integrating detectors and dual-exposure techniques for...
Hybrid simulation of breast CT for assessing microcalcification detectability [0.03%]
用于评价微钙化检测性的乳腺CT混合仿真
Su Hyun Lyu,Andrey Makeev,Dan Li et al.
Su Hyun Lyu et al.
Purpose: Virtual imaging trials (VITs) are of interest for regulatory evaluation because they enable faster and more cost-effective evaluation of new imaging technologies than patient clinical trials. Our purpose is to de...
Analysis of intra- and inter-observer variability in 4D liver ultrasound landmark labeling [0.03%]
四维肝超声标志定位的组内和组间变异性分析
Daniel Wulff,Floris Ernst
Daniel Wulff
Purpose: Four-dimensional (4D) ultrasound imaging is widely used in clinics for diagnostics and therapy guidance. Accurate target tracking in 4D ultrasound is crucial for autonomous therapy guidance systems, such as radio...
Bennett A Landman
Bennett A Landman
The editorial celebrates emerging breakthroughs and the foundational work that continues to shape the field. © 2025 Society of Photo-Optical Instrumenta...
Simulating dynamic tumor contrast enhancement in breast MRI using conditional generative adversarial networks [0.03%]
使用条件生成对抗网络模拟乳腺MRI中的动态肿瘤对比增强效应
Richard Osuala,Smriti Joshi,Apostolia Tsirikoglou et al.
Richard Osuala et al.
Purpose: Deep generative models and synthetic data generation have become essential for advancing computer-assisted diagnosis and treatment. We explore one such emerging and particularly promising application of deep gene...
Artificial intelligence in medical imaging diagnosis: are we ready for its clinical implementation? [0.03%]
人工智能在医学影像诊断中的应用：我们准备好了吗？
Oscar Ramos-Soto,Itzel Aranguren,Manuel Carrillo M et al.
Oscar Ramos-Soto et al.
Purpose: We examine the transformative potential of artificial intelligence (AI) in medical imaging diagnosis, focusing on improving diagnostic accuracy and efficiency through advanced algorithms. It addresses the signifi...
Bohan Jiang,Andrew J McNeil,Yihao Liu et al.
Bohan Jiang et al.
Purpose: Mpox is a viral illness with symptoms similar to smallpox. A key clinical metric to monitor disease progression is the number of skin lesions. Manually counting mpox skin lesions is labor-intensive and susceptibl...
Contrast-enhanced spectral mammography demonstrates better inter-reader repeatability than digital mammography for screening breast cancer patients [0.03%]
对比增强光谱乳房摄影在乳腺癌筛查中的组内一致性优于数字化乳腺 X 线摄影
Alisa Mohebbi,Ali Abdi,Saeed Mohammadzadeh et al.
Alisa Mohebbi et al.
Purpose: Our purpose is to assess the inter-rater agreement between digital mammography (DM) and contrast-enhanced spectral mammography (CESM) in evaluating the Breast Imaging Reporting and Data System (BI-RADS) grading. ...
Exploring the impact of image restoration in simulating higher dose mammography: effects on the detectability of microcalcifications across different sizes using model observer analysis [0.03%]
基于模型观察者分析的不同大小微钙化的检测效果：模拟高剂量乳腺摄影中图像重建的影响
Renann F Brandão,Lucas E Soares,Lucas R Borges et al.
Renann F Brandão et al.
Purpose: Breast cancer is one of the leading causes of cancer-related deaths among women, and digital mammography plays a key role in screening and early detection. The radiation dose on mammographic exams directly influe...